Modeling of Mean-VaR portfolio optimization by risk tolerance when the utility function is quadratic

NASA Astrophysics Data System (ADS)

Sukono, Sidi, Pramono; Bon, Abdul Talib bin; Supian, Sudradjat

2017-03-01

The problems of investing in financial assets are to choose a combination of weighting a portfolio can be maximized return expectations and minimizing the risk. This paper discusses the modeling of Mean-VaR portfolio optimization by risk tolerance, when square-shaped utility functions. It is assumed that the asset return has a certain distribution, and the risk of the portfolio is measured using the Value-at-Risk (VaR). So, the process of optimization of the portfolio is done based on the model of Mean-VaR portfolio optimization model for the Mean-VaR done using matrix algebra approach, and the Lagrange multiplier method, as well as Khun-Tucker. The results of the modeling portfolio optimization is in the form of a weighting vector equations depends on the vector mean return vector assets, identities, and matrix covariance between return of assets, as well as a factor in risk tolerance. As an illustration of numeric, analyzed five shares traded on the stock market in Indonesia. Based on analysis of five stocks return data gained the vector of weight composition and graphics of efficient surface of portfolio. Vector composition weighting weights and efficient surface charts can be used as a guide for investors in decisions to invest.

Formation of the portfolio of high-rise construction projects on the basis of optimization of «risk-return» rate

NASA Astrophysics Data System (ADS)

Uvarova, Svetlana; Kutsygina, Olga; Smorodina, Elena; Gumba, Khuta

2018-03-01

The effectiveness and sustainability of an enterprise are based on the effectiveness and sustainability of its portfolio of projects. When creating a production program for a construction company based on a portfolio of projects and related to the planning and implementation of initiated organizational and economic changes, the problem of finding the optimal "risk-return" ratio of the program (portfolio of projects) is solved. The article proposes and approves the methodology of forming a portfolio of enterprise projects on the basis of the correspondence principle. Optimization of the portfolio of projects on the criterion of "risk-return" also contributes to the company's sustainability.

Stackelberg Game of Buyback Policy in Supply Chain with a Risk-Averse Retailer and a Risk-Averse Supplier Based on CVaR

PubMed Central

Zhou, Yanju; Chen, Qian; Chen, Xiaohong; Wang, Zongrun

2014-01-01

This paper considers a decentralized supply chain in which a single supplier sells a perishable product to a single retailer facing uncertain demand. We assume that the supplier and the retailer are both risk averse and utilize Conditional Value at Risk (CVaR), a risk measure method which is popularized in financial risk management, to estimate their risk attitude. We establish a buyback policy model based on Stackelberg game theory under considering supply chain members' risk preference and get the expressions of the supplier's optimal repurchase price and the retailer's optimal order quantity which are compared with those under risk neutral case. Finally, a numerical example is applied to simulate that model and prove related conclusions. PMID:25247605

Stackelberg game of buyback policy in supply chain with a risk-averse retailer and a risk-averse supplier based on CVaR.

PubMed

Zhou, Yanju; Chen, Qian; Chen, Xiaohong; Wang, Zongrun

2014-01-01

This paper considers a decentralized supply chain in which a single supplier sells a perishable product to a single retailer facing uncertain demand. We assume that the supplier and the retailer are both risk averse and utilize Conditional Value at Risk (CVaR), a risk measure method which is popularized in financial risk management, to estimate their risk attitude. We establish a buyback policy model based on Stackelberg game theory under considering supply chain members' risk preference and get the expressions of the supplier's optimal repurchase price and the retailer's optimal order quantity which are compared with those under risk neutral case. Finally, a numerical example is applied to simulate that model and prove related conclusions.

Towards Risk Based Design for NASA's Missions

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Barrientos, Francesca; Meshkat, Leila

2004-01-01

This paper describes the concept of Risk Based Design in the context of NASA s low volume, high cost missions. The concept of accounting for risk in the design lifecycle has been discussed and proposed under several research topics, including reliability, risk analysis, optimization, uncertainty, decision-based design, and robust design. This work aims to identify and develop methods to enable and automate a means to characterize and optimize risk, and use risk as a tradeable resource to make robust and reliable decisions, in the context of the uncertain and ambiguous stage of early conceptual design. This paper first presents a survey of the related topics explored in the design research community as they relate to risk based design. Then, a summary of the topics from the NASA-led Risk Colloquium is presented, followed by current efforts within NASA to account for risk in early design. Finally, a list of "risk elements", identified for early-phase conceptual design at NASA, is presented. The purpose is to lay the foundation and develop a roadmap for future work and collaborations for research to eliminate and mitigate these risk elements in early phase design.

A gEUD-based inverse planning technique for HDR prostate brachytherapy: Feasibility study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giantsoudi, D.; Department of Radiation Oncology, Francis H. Burr Proton Therapy Center, Boston, Massachusetts 02114; Baltas, D.

2013-04-15

Purpose: The purpose of this work was to study the feasibility of a new inverse planning technique based on the generalized equivalent uniform dose for image-guided high dose rate (HDR) prostate cancer brachytherapy in comparison to conventional dose-volume based optimization. Methods: The quality of 12 clinical HDR brachytherapy implants for prostate utilizing HIPO (Hybrid Inverse Planning Optimization) is compared with alternative plans, which were produced through inverse planning using the generalized equivalent uniform dose (gEUD). All the common dose-volume indices for the prostate and the organs at risk were considered together with radiobiological measures. The clinical effectiveness of the differentmore » dose distributions was investigated by comparing dose volume histogram and gEUD evaluators. Results: Our results demonstrate the feasibility of gEUD-based inverse planning in HDR brachytherapy implants for prostate. A statistically significant decrease in D{sub 10} or/and final gEUD values for the organs at risk (urethra, bladder, and rectum) was found while improving dose homogeneity or dose conformity of the target volume. Conclusions: Following the promising results of gEUD-based optimization in intensity modulated radiation therapy treatment optimization, as reported in the literature, the implementation of a similar model in HDR brachytherapy treatment plan optimization is suggested by this study. The potential of improved sparing of organs at risk was shown for various gEUD-based optimization parameter protocols, which indicates the ability of this method to adapt to the user's preferences.« less

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Saile, Lynn; Freire de Carvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2011-01-01

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

Virtually optimized insoles for offloading the diabetic foot: A randomized crossover study.

PubMed

Telfer, S; Woodburn, J; Collier, A; Cavanagh, P R

2017-07-26

Integration of objective biomechanical measures of foot function into the design process for insoles has been shown to provide enhanced plantar tissue protection for individuals at-risk of plantar ulceration. The use of virtual simulations utilizing numerical modeling techniques offers a potential approach to further optimize these devices. In a patient population at-risk of foot ulceration, we aimed to compare the pressure offloading performance of insoles that were optimized via numerical simulation techniques against shape-based devices. Twenty participants with diabetes and at-risk feet were enrolled in this study. Three pairs of personalized insoles: one based on shape data and subsequently manufactured via direct milling; and two were based on a design derived from shape, pressure, and ultrasound data which underwent a finite element analysis-based virtual optimization procedure. For the latter set of insole designs, one pair was manufactured via direct milling, and a second pair was manufactured through 3D printing. The offloading performance of the insoles was analyzed for forefoot regions identified as having elevated plantar pressures. In 88% of the regions of interest, the use of virtually optimized insoles resulted in lower peak plantar pressures compared to the shape-based devices. Overall, the virtually optimized insoles significantly reduced peak pressures by a mean of 41.3kPa (p<0.001, 95% CI [31.1, 51.5]) for milled and 40.5kPa (p<0.001, 95% CI [26.4, 54.5]) for printed devices compared to shape-based insoles. The integration of virtual optimization into the insole design process resulted in improved offloading performance compared to standard, shape-based devices. ISRCTN19805071, www.ISRCTN.org. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk assessment and adaptive runoff utilization in water resource system considering the complex relationship among water supply, electricity generation and environment

NASA Astrophysics Data System (ADS)

Zhou, J.; Zeng, X.; Mo, L.; Chen, L.; Jiang, Z.; Feng, Z.; Yuan, L.; He, Z.

2017-12-01

Generally, the adaptive utilization and regulation of runoff in the source region of China's southwest rivers is classified as a typical multi-objective collaborative optimization problem. There are grim competitions and incidence relation in the subsystems of water supply, electricity generation and environment, which leads to a series of complex problems represented by hydrological process variation, blocked electricity output and water environment risk. Mathematically, the difficulties of multi-objective collaborative optimization focus on the description of reciprocal relationships and the establishment of evolving model of adaptive systems. Thus, based on the theory of complex systems science, this project tries to carry out the research from the following aspects: the changing trend of coupled water resource, the covariant factor and driving mechanism, the dynamic evolution law of mutual feedback dynamic process in the supply-generation-environment coupled system, the environmental response and influence mechanism of coupled mutual feedback water resource system, the relationship between leading risk factor and multiple risk based on evolutionary stability and dynamic balance, the transfer mechanism of multiple risk response with the variation of the leading risk factor, the multidimensional coupled feedback system of multiple risk assessment index system and optimized decision theory. Based on the above-mentioned research results, the dynamic method balancing the efficiency of multiple objectives in the coupled feedback system and optimized regulation model of water resources is proposed, and the adaptive scheduling mode considering the internal characteristics and external response of coupled mutual feedback system of water resource is established. In this way, the project can make a contribution to the optimal scheduling theory and methodology of water resource management under uncertainty in the source region of Southwest River.

Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations

NASA Astrophysics Data System (ADS)

Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying

2010-09-01

Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).

A Model for Determining Optimal Governance Structure in DoD Acquisition Projects in a Performance-Based Environment

DTIC Science & Technology

2011-03-09

task stability, technology application certainty, risk, and transaction-specific investments impact the selection of the optimal mode of governance...technology application certainty, risk, and transaction-specific investments impact the selection of the optimal mode of governance. Our model views...U.S. Defense Industry. The 1990s were a perfect storm of technological change, consolidation , budget downturns, environmental uncertainty, and the

Economic optimization of natural hazard protection - conceptual study of existing approaches

NASA Astrophysics Data System (ADS)

Spackova, Olga; Straub, Daniel

2013-04-01

Risk-based planning of protection measures against natural hazards has become a common practice in many countries. The selection procedure aims at identifying an economically efficient strategy with regard to the estimated costs and risk (i.e. expected damage). A correct setting of the evaluation methodology and decision criteria should ensure an optimal selection of the portfolio of risk protection measures under a limited state budget. To demonstrate the efficiency of investments, indicators such as Benefit-Cost Ratio (BCR), Marginal Costs (MC) or Net Present Value (NPV) are commonly used. However, the methodologies for efficiency evaluation differ amongst different countries and different hazard types (floods, earthquakes etc.). Additionally, several inconsistencies can be found in the applications of the indicators in practice. This is likely to lead to a suboptimal selection of the protection strategies. This study provides a general formulation for optimization of the natural hazard protection measures from a socio-economic perspective. It assumes that all costs and risks can be expressed in monetary values. The study regards the problem as a discrete hierarchical optimization, where the state level sets the criteria and constraints, while the actual optimization is made on the regional level (towns, catchments) when designing particular protection measures and selecting the optimal protection level. The study shows that in case of an unlimited budget, the task is quite trivial, as it is sufficient to optimize the protection measures in individual regions independently (by minimizing the sum of risk and cost). However, if the budget is limited, the need for an optimal allocation of resources amongst the regions arises. To ensure this, minimum values of BCR or MC can be required by the state, which must be achieved in each region. The study investigates the meaning of these indicators in the optimization task at the conceptual level and compares their suitability. To illustrate the theoretical findings, the indicators are tested on a hypothetical example of five regions with different risk levels. Last but not least, political and societal aspects and limitations in the use of the risk-based optimization framework are discussed.

Assessment of Medical Risks and Optimization of their Management using Integrated Medical Model

NASA Technical Reports Server (NTRS)

Fitts, Mary A.; Madurai, Siram; Butler, Doug; Kerstman, Eric; Risin, Diana

2008-01-01

The Integrated Medical Model (IMM) Project is a software-based technique that will identify and quantify the medical needs and health risks of exploration crew members during space flight and evaluate the effectiveness of potential mitigation strategies. The IMM Project employs an evidence-based approach that will quantify probability and consequences of defined in-flight medical risks, mitigation strategies, and tactics to optimize crew member health. Using stochastic techniques, the IMM will ultimately inform decision makers at both programmatic and institutional levels and will enable objective assessment of crew health and optimization of mission success using data from relevant cohort populations and from the astronaut population. The objectives of the project include: 1) identification and documentation of conditions that may occur during exploration missions (Baseline Medical Conditions List [BMCL), 2) assessment of the likelihood of conditions in the BMCL occurring during exploration missions (incidence rate), 3) determination of the risk associated with these conditions and quantify in terms of end states (Loss of Crew, Loss of Mission, Evacuation), 4) optimization of in-flight hardware mass, volume, power, bandwidth and cost for a given level of risk or uncertainty, and .. validation of the methodologies used.

Human health risk constrained naphthalene-contaminated groundwater remediation management through an improved credibility method.

PubMed

Li, Jing; Lu, Hongwei; Fan, Xing; Chen, Yizhong

2017-07-01

In this study, a human health risk constrained groundwater remediation management program based on the improved credibility is developed for naphthalene contamination. The program integrates simulation, multivariate regression analysis, health risk assessment, uncertainty analysis, and nonlinear optimization into a general framework. The improved credibility-based optimization model for groundwater remediation management with consideration of human health risk (ICOM-HHR) is capable of not only effectively addressing parameter uncertainties and risk-exceeding possibility in human health risk but also providing a credibility level that indicates the satisfaction of the optimal groundwater remediation strategies with multiple contributions of possibility and necessity. The capabilities and effectiveness of ICOM-HHR are illustrated through a real-world case study in Anhui Province, China. Results indicate that the ICOM-HHR would generate double remediation cost yet reduce approximately 10 times of the naphthalene concentrations at monitoring wells, i.e., mostly less than 1 μg/L, which implies that the ICOM-HHR usually results in better environmental and health risk benefits. And it is acceptable to obtain a better environmental quality and a lower health risk level with sacrificing a certain economic benefit.

Research and application of borehole structure optimization based on pre-drill risk assessment

NASA Astrophysics Data System (ADS)

Zhang, Guohui; Liu, Xinyun; Chenrong; Hugui; Yu, Wenhua; Sheng, Yanan; Guan, Zhichuan

2017-11-01

Borehole structure design based on pre-drill risk assessment and considering risks related to drilling operation is the pre-condition for safe and smooth drilling operation. Major risks of drilling operation include lost circulation, blowout, sidewall collapsing, sticking and failure of drilling tools etc. In the study, studying data from neighboring wells was used to calculate the profile of formation pressure with credibility in the target well, then the borehole structure design for the target well assessment by using the drilling risk assessment to predict engineering risks before drilling. Finally, the prediction results were used to optimize borehole structure design to prevent such drilling risks. The newly-developed technique provides a scientific basis for lowering probability and frequency of drilling engineering risks, and shortening time required to drill a well, which is of great significance for safe and high-efficient drilling.

Mean-variance model for portfolio optimization with background risk based on uncertainty theory

NASA Astrophysics Data System (ADS)

Zhai, Jia; Bai, Manying

2018-04-01

The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.

Spatial Optimization of Future Urban Development with Regards to Climate Risk and Sustainability Objectives.

PubMed

Caparros-Midwood, Daniel; Barr, Stuart; Dawson, Richard

2017-11-01

Future development in cities needs to manage increasing populations, climate-related risks, and sustainable development objectives such as reducing greenhouse gas emissions. Planners therefore face a challenge of multidimensional, spatial optimization in order to balance potential tradeoffs and maximize synergies between risks and other objectives. To address this, a spatial optimization framework has been developed. This uses a spatially implemented genetic algorithm to generate a set of Pareto-optimal results that provide planners with the best set of trade-off spatial plans for six risk and sustainability objectives: (i) minimize heat risks, (ii) minimize flooding risks, (iii) minimize transport travel costs to minimize associated emissions, (iv) maximize brownfield development, (v) minimize urban sprawl, and (vi) prevent development of greenspace. The framework is applied to Greater London (U.K.) and shown to generate spatial development strategies that are optimal for specific objectives and differ significantly from the existing development strategies. In addition, the analysis reveals tradeoffs between different risks as well as between risk and sustainability objectives. While increases in heat or flood risk can be avoided, there are no strategies that do not increase at least one of these. Tradeoffs between risk and other sustainability objectives can be more severe, for example, minimizing heat risk is only possible if future development is allowed to sprawl significantly. The results highlight the importance of spatial structure in modulating risks and other sustainability objectives. However, not all planning objectives are suited to quantified optimization and so the results should form part of an evidence base to improve the delivery of risk and sustainability management in future urban development. © 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Optimism and depression: a new look at social support as a mediator among women at risk for breast cancer.

PubMed

Garner, Melissa J; McGregor, Bonnie A; Murphy, Karly M; Koenig, Alex L; Dolan, Emily D; Albano, Denise

2015-12-01

Breast cancer risk is a chronic stressor associated with depression. Optimism is associated with lower levels of depression among breast cancer survivors. However, to our knowledge, no studies have explored the relationship between optimism and depression among women at risk for breast cancer. We hypothesized that women at risk for breast cancer who have higher levels of optimism would report lower levels of depression and that social support would mediate this relationship. Participants (N = 199) with elevated distress were recruited from the community and completed self-report measures of depression, optimism, and social support. Participants were grouped based on their family history of breast cancer. Path analysis was used to examine the cross-sectional relationship between optimism, social support, and depressive symptoms in each group. Results indicated that the variance in depressive symptoms was partially explained through direct paths from optimism and social support among women with a family history of breast cancer. The indirect path from optimism to depressive symptoms via social support was significant (β = -.053; 90% CI = -.099 to -.011, p = .037) in this group. However, among individuals without a family history of breast cancer, the indirect path from optimism to depressive symptoms via social support was not significant. These results suggest that social support partially mediates the relationship between optimism and depression among women at risk for breast cancer. Social support may be an important intervention target to reduce depression among women at risk for breast cancer. Copyright © 2015 John Wiley & Sons, Ltd.

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki

2013-01-01

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Portfolio optimization using median-variance approach

NASA Astrophysics Data System (ADS)

Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

2013-04-01

Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

Swarm intelligence applied to the risk evaluation for congenital heart surgery.

PubMed

Zapata-Impata, Brayan S; Ruiz-Fernandez, Daniel; Monsalve-Torra, Ana

2015-01-01

Particle Swarm Optimization is an optimization technique based on the positions of several particles created to find the best solution to a problem. In this work we analyze the accuracy of a modification of this algorithm to classify the levels of risk for a surgery, used as a treatment to correct children malformations that imply congenital heart diseases.

An optimization-based approach for facility energy management with uncertainties, and, Power portfolio optimization in deregulated electricity markets with risk management

NASA Astrophysics Data System (ADS)

Xu, Jun

Topic 1. An Optimization-Based Approach for Facility Energy Management with Uncertainties. Effective energy management for facilities is becoming increasingly important in view of the rising energy costs, the government mandate on the reduction of energy consumption, and the human comfort requirements. This part of dissertation presents a daily energy management formulation and the corresponding solution methodology for HVAC systems. The problem is to minimize the energy and demand costs through the control of HVAC units while satisfying human comfort, system dynamics, load limit constraints, and other requirements. The problem is difficult in view of the fact that the system is nonlinear, time-varying, building-dependent, and uncertain; and that the direct control of a large number of HVAC components is difficult. In this work, HVAC setpoints are the control variables developed on top of a Direct Digital Control (DDC) system. A method that combines Lagrangian relaxation, neural networks, stochastic dynamic programming, and heuristics is developed to predict the system dynamics and uncontrollable load, and to optimize the setpoints. Numerical testing and prototype implementation results show that our method can effectively reduce total costs, manage uncertainties, and shed the load, is computationally efficient. Furthermore, it is significantly better than existing methods. Topic 2. Power Portfolio Optimization in Deregulated Electricity Markets with Risk Management. In a deregulated electric power system, multiple markets of different time scales exist with various power supply instruments. A load serving entity (LSE) has multiple choices from these instruments to meet its load obligations. In view of the large amount of power involved, the complex market structure, risks in such volatile markets, stringent constraints to be satisfied, and the long time horizon, a power portfolio optimization problem is of critical importance but difficulty for an LSE to serve the load, maximize its profit, and manage risks. In this topic, a mid-term power portfolio optimization problem with risk management is presented. Key instruments are considered, risk terms based on semi-variances of spot market transactions are introduced, and penalties on load obligation violations are added to the objective function to improve algorithm convergence and constraint satisfaction. To overcome the inseparability of the resulting problem, a surrogate optimization framework is developed enabling a decomposition and coordination approach. Numerical testing results show that our method effectively provides decisions for various instruments to maximize profit, manage risks, and is computationally efficient.

Inflammatory and Other Biomarkers: Role in Pathophysiology and Prediction of Gestational Diabetes Mellitus

PubMed Central

Abell, Sally K.; De Courten, Barbora; Boyle, Jacqueline A.; Teede, Helena J.

2015-01-01

Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM. PMID:26110385

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

The case for risk-based premiums in public health insurance.

PubMed

Zweifel, Peter; Breuer, Michael

2006-04-01

Uniform, risk-independent insurance premiums are accepted as part of 'managed competition' in health care. However, they are not compatible with optimality of health insurance contracts in the presence of both ex ante and ex post moral hazard. They have adverse effects on insurer behaviour even if risk adjustment is taken into account. Risk-based premiums combined with means-tested, tax-financed transfers are advocated as an alternative.

A Study on the Optimal Generation Mix Based on Portfolio Theory with Considering the Basic Condition for Power Supply

NASA Astrophysics Data System (ADS)

Kato, Moritoshi; Zhou, Yicheng

This paper presents a novel method to analyze the optimal generation mix based on portfolio theory with considering the basic condition for power supply, which means that electricity generation corresponds with load curve. The optimization of portfolio is integrated with the calculation of a capacity factor of each generation in order to satisfy the basic condition for power supply. Besides, each generation is considered to be an asset, and risks of the generation asset both in its operation period and construction period are considered. Environmental measures are evaluated through restriction of CO2 emissions, which are indicated by CO2 price. Numerical examples show the optimal generation mix according to risks such as the deviation of capacity factor of nuclear power or restriction of CO2 emissions, the possibility of introduction of clean coal technology (IGCC, CCS) or renewable energy, and so on. The results of this work will be possibly applied as setting the target of the generation mix for the future according to prospects of risks of each generation and restrictions of CO2 emissions.

Mean-variance portfolio optimization by using time series approaches based on logarithmic utility function

NASA Astrophysics Data System (ADS)

Soeryana, E.; Fadhlina, N.; Sukono; Rusyaman, E.; Supian, S.

2017-01-01

Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on logarithmic utility function. Non constant mean analysed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analysed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyse some Islamic stocks in Indonesia. The expected result is to get the proportion of investment in each Islamic stock analysed.

Mean-Variance portfolio optimization by using non constant mean and volatility based on the negative exponential utility function

NASA Astrophysics Data System (ADS)

Soeryana, Endang; Halim, Nurfadhlina Bt Abdul; Sukono, Rusyaman, Endang; Supian, Sudradjat

2017-03-01

Investments in stocks investors are also faced with the issue of risk, due to daily price of stock also fluctuate. For minimize the level of risk, investors usually forming an investment portfolio. Establishment of a portfolio consisting of several stocks are intended to get the optimal composition of the investment portfolio. This paper discussed about optimizing investment portfolio of Mean-Variance to stocks by using mean and volatility is not constant based on the Negative Exponential Utility Function. Non constant mean analyzed using models Autoregressive Moving Average (ARMA), while non constant volatility models are analyzed using the Generalized Autoregressive Conditional heteroscedastic (GARCH). Optimization process is performed by using the Lagrangian multiplier technique. As a numerical illustration, the method is used to analyze some stocks in Indonesia. The expected result is to get the proportion of investment in each stock analyzed

Breast Cancer Screening in the Precision Medicine Era: Risk-Based Screening in a Population-Based Trial.

PubMed

Shieh, Yiwey; Eklund, Martin; Madlensky, Lisa; Sawyer, Sarah D; Thompson, Carlie K; Stover Fiscalini, Allison; Ziv, Elad; Van't Veer, Laura J; Esserman, Laura J; Tice, Jeffrey A

2017-01-01

Ongoing controversy over the optimal approach to breast cancer screening has led to discordant professional society recommendations, particularly in women age 40 to 49 years. One potential solution is risk-based screening, where decisions around the starting age, stopping age, frequency, and modality of screening are based on individual risk to maximize the early detection of aggressive cancers and minimize the harms of screening through optimal resource utilization. We present a novel approach to risk-based screening that integrates clinical risk factors, breast density, a polygenic risk score representing the cumulative effects of genetic variants, and sequencing for moderate- and high-penetrance germline mutations. We demonstrate how thresholds of absolute risk estimates generated by our prediction tools can be used to stratify women into different screening strategies (biennial mammography, annual mammography, annual mammography with adjunctive magnetic resonance imaging, defer screening at this time) while informing the starting age of screening for women age 40 to 49 years. Our risk thresholds and corresponding screening strategies are based on current evidence but need to be tested in clinical trials. The Women Informed to Screen Depending On Measures of risk (WISDOM) Study, a pragmatic, preference-tolerant randomized controlled trial of annual vs personalized screening, will study our proposed approach. WISDOM will evaluate the efficacy, safety, and acceptability of risk-based screening beginning in the fall of 2016. The adaptive design of this trial allows continued refinement of our risk thresholds as the trial progresses, and we discuss areas where we anticipate emerging evidence will impact our approach. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Design Tool Using a New Optimization Method Based on a Stochastic Process

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki; Yamaguchi, Katsuhito; Ishikawa, Yoshio

Conventional optimization methods are based on a deterministic approach since their purpose is to find out an exact solution. However, such methods have initial condition dependence and the risk of falling into local solution. In this paper, we propose a new optimization method based on the concept of path integrals used in quantum mechanics. The method obtains a solution as an expected value (stochastic average) using a stochastic process. The advantages of this method are that it is not affected by initial conditions and does not require techniques based on experiences. We applied the new optimization method to a hang glider design. In this problem, both the hang glider design and its flight trajectory were optimized. The numerical calculation results prove that performance of the method is sufficient for practical use.

Optimal combination treatment and vascular outcomes in recent ischemic stroke patients by premorbid risk level.

PubMed

Park, Jong-Ho; Ovbiagele, Bruce

2015-08-15

Optimal combination of secondary stroke prevention treatment including antihypertensives, antithrombotic agents, and lipid modifiers is associated with reduced recurrent vascular risk including stroke. It is unclear whether optimal combination treatment has a differential impact on stroke patients based on level of vascular risk. We analyzed a clinical trial dataset comprising 3680 recent non-cardioembolic stroke patients aged ≥35 years and followed for 2 years. Patients were categorized by appropriateness levels 0 to III depending on the number of the drugs prescribed divided by the number of drugs potentially indicated for each patient (0=none of the indicated medications prescribed and III=all indicated medications prescribed [optimal combination treatment]). High-risk was defined as having a history of stroke or coronary heart disease (CHD) prior to the index stroke event. Independent associations of medication appropriateness level with a major vascular event (stroke, CHD, or vascular death), ischemic stroke, and all-cause death were analyzed. Compared with level 0, for major vascular events, the HR of level III in the low-risk group was 0.51 (95% CI: 0.20-1.28) and 0.32 (0.14-0.70) in the high-risk group; for stroke, the HR of level III in the low-risk group was 0.54 (0.16-1.77) and 0.25 (0.08-0.85) in the high-risk group; and for all-cause death, the HR of level III in the low-risk group was 0.66 (0.09-5.00) and 0.22 (0.06-0.78) in the high-risk group. Optimal combination treatment is related to a significantly lower risk of future vascular events and death among high-risk patients after a recent non-cardioembolic stroke. Copyright © 2015 Elsevier B.V. All rights reserved.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

PubMed

Yan, Aijun; Liu, Sanyang; Dong, Xiaojuan

2016-01-01

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

Risk Reduction and Resource Pooling on a Cooperation Task

ERIC Educational Resources Information Center

Pietras, Cynthia J.; Cherek, Don R.; Lane, Scott D.; Tcheremissine, Oleg

2006-01-01

Two experiments investigated choice in adult humans on a simulated cooperation task to evaluate a risk-reduction account of sharing based on the energy-budget rule. The energy-budget rule is an optimal foraging model that predicts risk-averse choices when net energy gains exceed energy requirements (positive energy budget) and risk-prone choices…

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

The Role of Nuclear Power in Reducing Risk of the Fossil Fuel Prices and Diversity of Electricity Generation in Tunisia: A Portfolio Approach

NASA Astrophysics Data System (ADS)

Abdelhamid, Mohamed Ben; Aloui, Chaker; Chaton, Corinne; Souissi, Jomâa

2010-04-01

This paper applies real options and mean-variance portfolio theories to analyze the electricity generation planning into presence of nuclear power plant for the Tunisian case. First, we analyze the choice between fossil fuel and nuclear production. A dynamic model is presented to illustrate the impact of fossil fuel cost uncertainty on the optimal timing to switch from gas to nuclear. Next, we use the portfolio theory to manage risk of the electricity generation portfolio and to determine the optimal fuel mix with the nuclear alternative. Based on portfolio theory, the results show that there is other optimal mix than the mix fixed for the Tunisian mix for the horizon 2010-2020, with lower cost for the same risk degree. In the presence of nuclear technology, we found that the optimal generating portfolio must include 13% of nuclear power technology share.

Safer passenger car front shapes for pedestrians: A computational approach to reduce overall pedestrian injury risk in realistic impact scenarios.

PubMed

Li, Guibing; Yang, Jikuang; Simms, Ciaran

2017-03-01

Vehicle front shape has a significant influence on pedestrian injuries and the optimal design for overall pedestrian protection remains an elusive goal, especially considering the variability of vehicle-to-pedestrian accident scenarios. Therefore this study aims to develop and evaluate an efficient framework for vehicle front shape optimization for pedestrian protection accounting for the broad range of real world impact scenarios and their distributions in recent accident data. Firstly, a framework for vehicle front shape optimization for pedestrian protection was developed based on coupling of multi-body simulations and a genetic algorithm. This framework was then applied for optimizing passenger car front shape for pedestrian protection, and its predictions were evaluated using accident data and kinematic analyses. The results indicate that the optimization shows a good convergence and predictions of the optimization framework are corroborated when compared to the available accident data, and the optimization framework can distinguish 'good' and 'poor' vehicle front shapes for pedestrian safety. Thus, it is feasible and reliable to use the optimization framework for vehicle front shape optimization for reducing overall pedestrian injury risk. The results also show the importance of considering the broad range of impact scenarios in vehicle front shape optimization. A safe passenger car for overall pedestrian protection should have a wide and flat bumper (covering pedestrians' legs from the lower leg up to the shaft of the upper leg with generally even contacts), a bonnet leading edge height around 750mm, a short bonnet (<800mm) with a shallow or steep angle (either >17° or <12°) and a shallow windscreen (≤30°). Sensitivity studies based on simulations at the population level indicate that the demands for a safe passenger car front shape for head and leg protection are generally consistent, but partially conflict with pelvis protection. In particular, both head and leg injury risk increase with increasing bumper lower height and depth, and decrease with increasing bonnet leading edge height, while pelvis injury risk increases with increasing bonnet leading edge height. However, the effects of bonnet leading edge height and windscreen design on head injury risk are complex and require further analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Tool for Designing Engineering Systems Using a New Optimization Method Based on a Stochastic Process

NASA Astrophysics Data System (ADS)

Yoshida, Hiroaki; Yamaguchi, Katsuhito; Ishikawa, Yoshio

The conventional optimization methods were based on a deterministic approach, since their purpose is to find out an exact solution. However, these methods have initial condition dependence and risk of falling into local solution. In this paper, we propose a new optimization method based on a concept of path integral method used in quantum mechanics. The method obtains a solutions as an expected value (stochastic average) using a stochastic process. The advantages of this method are not to be affected by initial conditions and not to need techniques based on experiences. We applied the new optimization method to a design of the hang glider. In this problem, not only the hang glider design but also its flight trajectory were optimized. The numerical calculation results showed that the method has a sufficient performance.

Robust optimization-based DC optimal power flow for managing wind generation uncertainty

NASA Astrophysics Data System (ADS)

Boonchuay, Chanwit; Tomsovic, Kevin; Li, Fangxing; Ongsakul, Weerakorn

2012-11-01

Integrating wind generation into the wider grid causes a number of challenges to traditional power system operation. Given the relatively large wind forecast errors, congestion management tools based on optimal power flow (OPF) need to be improved. In this paper, a robust optimization (RO)-based DCOPF is proposed to determine the optimal generation dispatch and locational marginal prices (LMPs) for a day-ahead competitive electricity market considering the risk of dispatch cost variation. The basic concept is to use the dispatch to hedge against the possibility of reduced or increased wind generation. The proposed RO-based DCOPF is compared with a stochastic non-linear programming (SNP) approach on a modified PJM 5-bus system. Primary test results show that the proposed DCOPF model can provide lower dispatch cost than the SNP approach.

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location-Specific Premiums in the Netherlands.

PubMed

Ermolieva, T; Filatova, T; Ermoliev, Y; Obersteiner, M; de Bruijn, K M; Jeuken, A

2017-01-01

As flood risks grow worldwide, a well-designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood-loss-sharing program involving private insurance based on location-specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS-based flood model and a stochastic optimization procedure with respect to location-specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile-related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures. © 2016 Society for Risk Analysis.

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATLmore » Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.« less

A novel applicator design for intracavitary brachytherapy of the nasopharynx: Simulated reconstruction, image-guided adaptive brachytherapy planning, and dosimetry.

PubMed

Bacorro, Warren R; Agas, Ryan Anthony F; Cabrera, Stellar Marie R; Bojador, Maureen R; Sogono, Paolo G; Mejia, Michael Benedict A; Sy Ortin, Teresa T

2018-05-11

In nasopharyngeal cancer, brachytherapy is given as boost in primary treatment or as salvage for recurrent or persistent disease. The Rotterdam nasopharyngeal applicator (RNA) allows for suboptimal reduction of soft palate radiation dose, based on image-guided brachytherapy plans. Building on the RNA, we propose a novel design, the Benavides nasopharyngeal applicator (BNA). The virtual BNA was reconstructed on two cases (one T1, one T2) previously treated with intracavitary brachytherapy using the RNA. Dose was prescribed to the high-risk clinical target volumes (CTVs) and optimization was such that high-risk CTV D90 ≥ 100% of prescribed dose (PD), intermediate-risk-CTV D90 ≥ 75% PD, and soft palate D2cc ≤ 120% PD. The optimized RNA and BNA image-guided brachytherapy plans were compared in terms of CTV coverage and organs-at-risk sparing. Optimization objectives were more easily met with the BNA. For the T1 case, all three planning objectives were easily achieved in both the RNA and BNA, but with 18-19% lower soft palate doses with the BNA. For the T2 case, the CTV planning objectives were achieved in both the RNA and BNA, but the soft palate constraint was only achieved with the BNA, with 38-41% lower soft palate doses. Compared to the RNA, the BNA permits easier optimization and improves therapeutic ratio by a significant reduction of soft palate doses, based on simulation using a proposed system for CTV/organs-at-risk delineation, prescription, and optimization for image-guided adaptive brachytherapy. Clinical piloting using a prototype is necessary to evaluate its feasibility and utility. Copyright © 2018 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Comprehensive risk analysis for structure type selection.

DOT National Transportation Integrated Search

2010-04-01

Optimization of bridge selection and design traditionally has been sought in terms of the finished structure. This study presents a : more comprehensive risk-based analysis that includes user costs and accidents during the construction phase. Costs f...

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

NASA Astrophysics Data System (ADS)

Yang, Huanhuan; Gunzburger, Max

2017-06-01

Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk measure so that an ideal acoustic liner impedance is determined that is robust in the presence of uncertainties. A parallel reduced-order modeling framework is developed that dramatically improves the computational efficiency of the stochastic optimization solver for a realistic nacelle geometry. The reduced stochastic optimization solver takes less than 500 seconds to execute. In addition, well-posedness and finite element error analyses of the state system and optimization problem are provided.

Constrained optimization via simulation models for new product innovation

NASA Astrophysics Data System (ADS)

Pujowidianto, Nugroho A.

2017-11-01

We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

Assessing the Value of Information for Identifying Optimal Floodplain Management Portfolios

NASA Astrophysics Data System (ADS)

Read, L.; Bates, M.; Hui, R.; Lund, J. R.

2014-12-01

Floodplain management is a complex portfolio problem that can be analyzed from an integrated perspective incorporating traditionally structural and nonstructural options. One method to identify effective strategies for preparing, responding to, and recovering from floods is to optimize for a portfolio of temporary (emergency) and permanent floodplain management options. A risk-based optimization approach to this problem assigns probabilities to specific flood events and calculates the associated expected damages. This approach is currently limited by: (1) the assumption of perfect flood forecast information, i.e. implementing temporary management activities according to the actual flood event may differ from optimizing based on forecasted information and (2) the inability to assess system resilience across a range of possible future events (risk-centric approach). Resilience is defined here as the ability of a system to absorb and recover from a severe disturbance or extreme event. In our analysis, resilience is a system property that requires integration of physical, social, and information domains. This work employs a 3-stage linear program to identify the optimal mix of floodplain management options using conditional probabilities to represent perfect and imperfect flood stages (forecast vs. actual events). We assess the value of information in terms of minimizing damage costs for two theoretical cases - urban and rural systems. We use portfolio analysis to explore how the set of optimal management options differs depending on whether the goal is for the system to be risk-adverse to a specified event or resilient over a range of events.

Optimal environmental management strategy and implementation for groundwater contamination prevention and restoration.

PubMed

Wang, Mingyu

2006-04-01

An innovative management strategy is proposed for optimized and integrated environmental management for regional or national groundwater contamination prevention and restoration allied with consideration of sustainable development. This management strategy accounts for availability of limited resources, human health and ecological risks from groundwater contamination, costs for groundwater protection measures, beneficial uses and values from groundwater protection, and sustainable development. Six different categories of costs are identified with regard to groundwater prevention and restoration. In addition, different environmental impacts from groundwater contamination including human health and ecological risks are individually taken into account. System optimization principles are implemented to accomplish decision-makings on the optimal resources allocations of the available resources or budgets to different existing contaminated sites and projected contamination sites for a maximal risk reduction. Established management constraints such as budget limitations under different categories of costs are satisfied at the optimal solution. A stepwise optimization process is proposed in which the first step is to select optimally a limited number of sites where remediation or prevention measures will be taken, from all the existing contaminated and projected contamination sites, based on a total regionally or nationally available budget in a certain time frame such as 10 years. Then, several optimization steps determined year-by-year optimal distributions of the available yearly budgets for those selected sites. A hypothetical case study is presented to demonstrate a practical implementation of the management strategy. Several issues pertaining to groundwater contamination exposure and risk assessments and remediation cost evaluations are briefly discussed for adequately understanding implementations of the management strategy.

Model-based approach for quantitative estimates of skin, heart, and lung toxicity risk for left-side photon and proton irradiation after breast-conserving surgery.

PubMed

Tommasino, Francesco; Durante, Marco; D'Avino, Vittoria; Liuzzi, Raffaele; Conson, Manuel; Farace, Paolo; Palma, Giuseppe; Schwarz, Marco; Cella, Laura; Pacelli, Roberto

2017-05-01

Proton beam therapy represents a promising modality for left-side breast cancer (BC) treatment, but concerns have been raised about skin toxicity and poor cosmesis. The aim of this study is to apply skin normal tissue complication probability (NTCP) model for intensity modulated proton therapy (IMPT) optimization in left-side BC. Ten left-side BC patients undergoing photon irradiation after breast-conserving surgery were randomly selected from our clinical database. Intensity modulated photon (IMRT) and IMPT plans were calculated with iso-tumor-coverage criteria and according to RTOG 1005 guidelines. Proton plans were computed with and without skin optimization. Published NTCP models were employed to estimate the risk of different toxicity endpoints for skin, lung, heart and its substructures. Acute skin NTCP evaluation suggests a lower toxicity level with IMPT compared to IMRT when the skin is included in proton optimization strategy (0.1% versus 1.7%, p < 0.001). Dosimetric results show that, with the same level of tumor coverage, IMPT attains significant heart and lung dose sparing compared with IMRT. By NTCP model-based analysis, an overall reduction in the cardiopulmonary toxicity risk prediction can be observed for all IMPT compared to IMRT plans: the relative risk reduction from protons varies between 0.1 and 0.7 depending on the considered toxicity endpoint. Our analysis suggests that IMPT might be safely applied without increasing the risk of severe acute radiation induced skin toxicity. The quantitative risk estimates also support the potential clinical benefits of IMPT for left-side BC irradiation due to lower risk of cardiac and pulmonary morbidity. The applied approach might be relevant on the long term for the setup of cost-effectiveness evaluation strategies based on NTCP predictions.

An integrated simulation and optimization approach for managing human health risks of atmospheric pollutants by coal-fired power plants.

PubMed

Dai, C; Cai, X H; Cai, Y P; Guo, H C; Sun, W; Tan, Q; Huang, G H

2014-06-01

This research developed a simulation-aided nonlinear programming model (SNPM). This model incorporated the consideration of pollutant dispersion modeling, and the management of coal blending and the related human health risks within a general modeling framework In SNPM, the simulation effort (i.e., California puff [CALPUFF]) was used to forecast the fate of air pollutants for quantifying the health risk under various conditions, while the optimization studies were to identify the optimal coal blending strategies from a number of alternatives. To solve the model, a surrogate-based indirect search approach was proposed, where the support vector regression (SVR) was used to create a set of easy-to-use and rapid-response surrogates for identifying the function relationships between coal-blending operating conditions and health risks. Through replacing the CALPUFF and the corresponding hazard quotient equation with the surrogates, the computation efficiency could be improved. The developed SNPM was applied to minimize the human health risk associated with air pollutants discharged from Gaojing and Shijingshan power plants in the west of Beijing. Solution results indicated that it could be used for reducing the health risk of the public in the vicinity of the two power plants, identifying desired coal blending strategies for decision makers, and considering a proper balance between coal purchase cost and human health risk. A simulation-aided nonlinear programming model (SNPM) is developed. It integrates the advantages of CALPUFF and nonlinear programming model. To solve the model, a surrogate-based indirect search approach based on the combination of support vector regression and genetic algorithm is proposed. SNPM is applied to reduce the health risk caused by air pollutants discharged from Gaojing and Shijingshan power plants in the west of Beijing. Solution results indicate that it is useful for generating coal blending schemes, reducing the health risk of the public, reflecting the trade-offbetween coal purchase cost and health risk.

Projecting School Psychology Staffing Needs Using a Risk-Adjusted Model.

ERIC Educational Resources Information Center

Stellwagen, Kurt

A model is proposed to project optimal school psychology service ratios based upon the percentages of at risk students enrolled within a given school population. Using the standard 1:1,000 service ratio advocated by The National Association of School Psychologists (NASP) as a starting point, ratios are then adjusted based upon the size of three…

Risk and utility in portfolio optimization

NASA Astrophysics Data System (ADS)

Cohen, Morrel H.; Natoli, Vincent D.

2003-06-01

Modern portfolio theory (MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk, conflating uncertainty with risk. There have been many subsequent attempts to alleviate that weakness which, typically, combine utility and risk. We present here a modification of MPT based on the inclusion of separate risk and utility criteria. We define risk as the probability of failure to meet a pre-established investment goal. We define utility as the expectation of a utility function with positive and decreasing marginal value as a function of yield. The emphasis throughout is on long investment horizons for which risk-free assets do not exist. Analytic results are presented for a Gaussian probability distribution. Risk-utility relations are explored via empirical stock-price data, and an illustrative portfolio is optimized using the empirical data.

The Integrated Medical Model - A Risk Assessment and Decision Support Tool for Human Space Flight Missions

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles G.; Saile, Lynn; FreiredeCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Lopez, Vilma

2010-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission planners and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight.

Degradation and Impurity Profile Study of Ciclopirox Olamine after Pre-column Derivatization: A Risk Based Approach.

PubMed

Baghel, Madhuri; Rajput, Sadhana

2017-10-01

The present study focus on ICH prescribed stress degradation of ciclopirox olamine after precolumn derivatization. For establishing stability-indicating assay, the reaction solutions in which different degradation products were formed were mixed, and the separation was optimized by applying principle of QbD. A risk-analysis tools based on cause-effect risk assessment matrix with control-noise-experimentation (CNX) approach was utilized for identifying the high risk variable affecting the analytical attributes. Plackett Burman and central composite design was then used to screen and optimize experimental variables for DOE studies to resolve ciclopirox olamine and four of its degradation related impurities with good peak asymmetry and theoretical plates using C18 column. The method was validated according to ICH and ISO guidelines. To ensure reliability of the result, evaluation of risk profile, combined standard uncertainty and expanded uncertainty were also studied. One process related and four unknown degradation products were identified and characterized by LC-MS/MS study. The degradation pathways of degradants were proposed based on m/z values. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme

NASA Astrophysics Data System (ADS)

Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin

2018-02-01

Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.

Research on regularized mean-variance portfolio selection strategy with modified Roy safety-first principle.

PubMed

Atta Mills, Ebenezer Fiifi Emire; Yan, Dawen; Yu, Bo; Wei, Xinyuan

2016-01-01

We propose a consolidated risk measure based on variance and the safety-first principle in a mean-risk portfolio optimization framework. The safety-first principle to financial portfolio selection strategy is modified and improved. Our proposed models are subjected to norm regularization to seek near-optimal stable and sparse portfolios. We compare the cumulative wealth of our preferred proposed model to a benchmark, S&P 500 index for the same period. Our proposed portfolio strategies have better out-of-sample performance than the selected alternative portfolio rules in literature and control the downside risk of the portfolio returns.

Cost-effectiveness of optimizing prevention in patients with coronary heart disease: the EUROASPIRE III health economics project.

PubMed

De Smedt, Delphine; Kotseva, Kornelia; De Bacquer, Dirk; Wood, David; De Backer, Guy; Dallongeville, Jean; Seppo, Lehto; Pajak, Andrzej; Reiner, Zeljko; Vanuzzo, Diego; Georgiev, Borislav; Gotcheva, Nina; Annemans, Lieven

2012-11-01

The EUROASPIRE III survey indicated that the guidelines on cardiovascular disease prevention are poorly implemented in patients with established coronary heart disease (CHD). The purpose of this health economic project was to assess the potential clinical effectiveness and cost-effectiveness of optimizing cardiovascular prevention in eight EUROASPIRE III countries (Belgium, Bulgaria, Croatia, Finland, France, Italy, Poland, and the U.K.). METHODS AND RESULTS The individual risk for subsequent cardiovascular events was estimated, based on published Framingham equations. Based on the EUROASPIRE III data, the type of suboptimal prevention, if any, was identified for each individual, and the effects of optimized tailored prevention (smoking cessation, diet and exercise, better management of elevated blood pressure and/or LDL-cholesterol) were estimated. Costs of prevention and savings of avoided events were based on country-specific data. A willingness to pay threshold of €30,000/quality-adjusted life year (QALY) was used. The robustness of the results was validated by sensitivity analyses. Overall, the cost-effectiveness analyses for the eight countries showed mainly favourable results with an average incremental cost-effectiveness ratio (ICER) of €12,484 per QALY. Only in the minority of patients at the lowest risk for recurrent events, intensifying preventive therapy seems not cost-effective. Also, the single impact of intensified cholesterol control seems less cost-effective, possibly because their initial 2-year risk was already fairly low, hence the room for improvement is rather limited. These results underscore the societal value of optimizing prevention in most patients with established CHD, but also highlight the need for setting priorities towards patients more at risk and the need for more studies comparing intensified prevention with usual care in these patients.

Urine albumin/creatinine ratio, high sensitivity C-reactive protein and N-terminal pro brain natriuretic peptide--three new cardiovascular risk markers--do they improve risk prediction and influence treatment?

PubMed

Olsen, Michael H; Sehestedt, Thomas; Lyngbaek, Stig; Hansen, Tine W; Rasmussen, Susanne; Wachtell, Kristian; Torp-Pedersen, Christian; Hildebrandt, Per R; Ibsen, Hans

2010-01-01

In order to prioritize limited health resources in a time of increasing demands optimal cardiovascular risk stratification is essential. We tested the additive prognostic value of 3 relatively new, but established cardiovascular risk markers: N-terminal pro brain natriuretic peptide (Nt-proBNP), related to hemodynamic cardiovascular risk factors, high sensitivity C-reactive protein (hsCRP), related to metabolic cardiovascular risk factors and urine albumin/creatinine ratio (UACR), related to hemodynamic as well as metabolic risk factors. In healthy subjects with a 10-year risk of cardiovascular death lower than 5% based on HeartScore and therefore not eligible for primary prevention, the actual 10-year risk of cardiovascular death exceeded 5% in a small subgroup of subjects with UACR higher than the 95-percentile of approximately 1.6 mg/mmol. Combined use of high UACR or high hsCRP identified a larger subgroup of 16% with high cardiovascular risk in which primary prevention may be advised despite low-moderate cardiovascular risk based on HeartScore. Furthermore, combined use of high UACR or high Nt-proBNP in subjects with known cardiovascular disease or diabetes identified a large subgroup of 48% with extremely high cardiovascular risk who should be referred for specialist care to optimize treatment.

Incentive-compatible guaranteed renewable health insurance premiums.

PubMed

Herring, Bradley; Pauly, Mark V

2006-05-01

Theoretical models of guaranteed renewable insurance display front-loaded premium schedules. Such schedules both cover lifetime total claims of low-risk and high-risk individuals and provide an incentive for those who remain low-risk to continue to purchase the policy. Questions have been raised of whether actual individual insurance markets in the US approximate the behavior predicted by these models, both because young consumers may not be able to "afford" front-loading and because insurers may behave strategically in ways that erode the value of protection against risk reclassification. In this paper, the optimal competitive age-based premium schedule for a benchmark guaranteed renewable health insurance policy is estimated using medical expenditure data. Several factors are shown to reduce the amount of front-loading necessary. Indeed, the resulting optimal premium path increases with age. Actual premium paths exhibited by purchasers of individual insurance are close to the optimal renewable schedule we estimate. Finally, consumer utility associated with the feature is examined.

A Risk-Based Multi-Objective Optimization Concept for Early-Warning Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Loschko, M.; Nowak, W.

2014-12-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources which cannot be eliminated, especially in urban regions. As matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs.In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations and the early warning time and to minimize the installation and operating costs of the monitoring network. A qualitative risk ranking is used to prioritize the known risk sources for monitoring. The unknown risk sources can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well.We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks which are valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrade) to also cover moderate, tolerable and unknown risk sources. Monitoring networks which are valid for the remaining risk also cover all other risk sources but the early-warning time suffers.The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. To avoid numerical dispersion during the transport simulations we use the particle-tracking random walk method.

Development of optimization-based probabilistic earthquake scenarios for the city of Tehran

NASA Astrophysics Data System (ADS)

Zolfaghari, M. R.; Peyghaleh, E.

2016-01-01

This paper presents the methodology and practical example for the application of optimization process to select earthquake scenarios which best represent probabilistic earthquake hazard in a given region. The method is based on simulation of a large dataset of potential earthquakes, representing the long-term seismotectonic characteristics in a given region. The simulation process uses Monte-Carlo simulation and regional seismogenic source parameters to generate a synthetic earthquake catalogue consisting of a large number of earthquakes, each characterized with magnitude, location, focal depth and fault characteristics. Such catalogue provides full distributions of events in time, space and size; however, demands large computation power when is used for risk assessment, particularly when other sources of uncertainties are involved in the process. To reduce the number of selected earthquake scenarios, a mixed-integer linear program formulation is developed in this study. This approach results in reduced set of optimization-based probabilistic earthquake scenario, while maintaining shape of hazard curves and full probabilistic picture by minimizing the error between hazard curves driven by full and reduced sets of synthetic earthquake scenarios. To test the model, the regional seismotectonic and seismogenic characteristics of northern Iran are used to simulate a set of 10,000-year worth of events consisting of some 84,000 earthquakes. The optimization model is then performed multiple times with various input data, taking into account probabilistic seismic hazard for Tehran city as the main constrains. The sensitivity of the selected scenarios to the user-specified site/return period error-weight is also assessed. The methodology could enhance run time process for full probabilistic earthquake studies like seismic hazard and risk assessment. The reduced set is the representative of the contributions of all possible earthquakes; however, it requires far less computation power. The authors have used this approach for risk assessment towards identification of effectiveness-profitability of risk mitigation measures, using optimization model for resource allocation. Based on the error-computation trade-off, 62-earthquake scenarios are chosen to be used for this purpose.

Particle swarm optimization based space debris surveillance network scheduling

NASA Astrophysics Data System (ADS)

Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao

2017-02-01

The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.

Optimal breastfeeding durations for HIV-exposed infants: the impact of maternal ART use, infant mortality and replacement feeding risk.

PubMed

Mallampati, Divya; MacLean, Rachel L; Shapiro, Roger; Dabis, Francois; Engelsmann, Barbara; Freedberg, Kenneth A; Leroy, Valeriane; Lockman, Shahin; Walensky, Rochelle; Rollins, Nigel; Ciaranello, Andrea

2018-04-01

In 2010, the WHO recommended women living with HIV breastfeed for 12 months while taking antiretroviral therapy (ART) to balance breastfeeding benefits against HIV transmission risks. To inform the 2016 WHO guidelines, we updated prior research on the impact of breastfeeding duration on HIV-free infant survival (HFS) by incorporating maternal ART duration, infant/child mortality and mother-to-child transmission data. Using the Cost-Effectiveness of Preventing AIDS Complications (CEPAC)-Infant model, we simulated the impact of breastfeeding duration on 24-month HFS among HIV-exposed, uninfected infants. We defined "optimal" breastfeeding durations as those maximizing 24-month HFS. We varied maternal ART duration, mortality rates among breastfed infants/children, and relative risk of mortality associated with replacement feeding ("RRRF"), modelled as a multiplier on all-cause mortality for replacement-fed infants/children (range: 1 [no additional risk] to 6). The base-case simulated RRRF = 3, median infant mortality, and 24-month maternal ART duration. In the base-case, HFS ranged from 83.1% (no breastfeeding) to 90.2% (12-months breastfeeding). Optimal breastfeeding durations increased with higher RRRF values and longer maternal ART durations, but did not change substantially with variation in infant mortality rates. Optimal breastfeeding durations often exceeded the previous WHO recommendation of 12 months. In settings with high RRRF and long maternal ART durations, HFS is maximized when mothers breastfeed longer than the previously-recommended 12 months. In settings with low RRRF or short maternal ART durations, shorter breastfeeding durations optimize HFS. If mothers are supported to use ART for longer periods of time, it is possible to reduce transmission risks and gain the benefits of longer breastfeeding durations. © 2018 The Authors. Journal of the International AIDS Society published by John Wiley & sons Ltd on behalf of the International AIDS Society.

Combinatorial Algorithms for Portfolio Optimization Problems - Case of Risk Moderate Investor

NASA Astrophysics Data System (ADS)

Juarna, A.

2017-03-01

Portfolio optimization problem is a problem of finding optimal combination of n stocks from N ≥ n available stocks that gives maximal aggregate return and minimal aggregate risk. In this paper given N = 43 from the IDX (Indonesia Stock Exchange) group of the 45 most-traded stocks, known as the LQ45, with p = 24 data of monthly returns for each stock, spanned over interval 2013-2014. This problem actually is a combinatorial one where its algorithm is constructed based on two considerations: risk moderate type of investor and maximum allowed correlation coefficient between every two eligible stocks. The main outputs resulted from implementation of the algorithms is a multiple curve of three portfolio’s attributes, e.g. the size, the ratio of return to risk, and the percentage of negative correlation coefficient for every two chosen stocks, as function of maximum allowed correlation coefficient between each two stocks. The output curve shows that the portfolio contains three stocks with ratio of return to risk at 14.57 if the maximum allowed correlation coefficient between every two eligible stocks is negative and contains 19 stocks with maximum allowed correlation coefficient 0.17 to get maximum ratio of return to risk at 25.48.

Site Selection and Resource Allocation of Oil Spill Emergency Base for Offshore Oil Facilities

NASA Astrophysics Data System (ADS)

Li, Yunbin; Liu, Jingxian; Wei, Lei; Wu, Weihuang

2018-02-01

Based on the analysis of the historical data about oil spill accidents in the Bohai Sea, this paper discretizes oil spilled source into a limited number of spill points. According to the probability of oil spill risk, the demand for salvage forces at each oil spill point is evaluated. Aiming at the specific location of the rescue base around the Bohai Sea, a cost-benefit analysis is conducted to determine the total cost of disasters for each rescue base. Based on the relationship between the oil spill point and the rescue site, a multi-objective optimization location model for the oil spill rescue base in the Bohai Sea region is established. And the genetic algorithm is used to solve the optimization problem, and determine the emergency rescue base optimization program and emergency resources allocation ratio.

Patient-centered clinical trials.

PubMed

Chaudhuri, Shomesh E; Ho, Martin P; Irony, Telba; Sheldon, Murray; Lo, Andrew W

2018-02-01

We apply Bayesian decision analysis (BDA) to incorporate patient preferences in the regulatory approval process for new therapies. By assigning weights to type I and type II errors based on patient preferences, the significance level (α) and power (1-β) of a randomized clinical trial (RCT) for a new therapy can be optimized to maximize the value to current and future patients and, consequently, to public health. We find that for weight-loss devices, potentially effective low-risk treatments have optimal αs larger than the traditional one-sided significance level of 5%, whereas potentially less effective and riskier treatments have optimal αs below 5%. Moreover, the optimal RCT design, including trial size, varies with the risk aversion and time-to-access preferences and the medical need of the target population. Copyright © 2017 Elsevier Ltd. All rights reserved.

The variance of length of stay and the optimal DRG outlier payments.

PubMed

Felder, Stefan

2009-09-01

Prospective payment schemes in health care often include supply-side insurance for cost outliers. In hospital reimbursement, prospective payments for patient discharges, based on their classification into diagnosis related group (DRGs), are complemented by outlier payments for long stay patients. The outlier scheme fixes the length of stay (LOS) threshold, constraining the profit risk of the hospitals. In most DRG systems, this threshold increases with the standard deviation of the LOS distribution. The present paper addresses the adequacy of this DRG outlier threshold rule for risk-averse hospitals with preferences depending on the expected value and the variance of profits. It first shows that the optimal threshold solves the hospital's tradeoff between higher profit risk and lower premium loading payments. It then demonstrates for normally distributed truncated LOS that the optimal outlier threshold indeed decreases with an increase in the standard deviation.

Inventory Control System for a Healthcare Apparel Service Centre with Stockout Risk: A Case Analysis

PubMed Central

Hui, Chi-Leung

2017-01-01

Based on the real-world inventory control problem of a capacitated healthcare apparel service centre in Hong Kong which provides tailor-made apparel-making services for the elderly and disabled people, this paper studies a partial backordered continuous review inventory control problem in which the product demand follows a Poisson process with a constant lead time. The system is controlled by an (Q,r) inventory policy which incorporate the stockout risk, storage capacity, and partial backlog. The healthcare apparel service centre, under the capacity constraint, aims to minimize the inventory cost and achieving a low stockout risk. To address this challenge, an optimization problem is constructed. A real case-based data analysis is conducted, and the result shows that the expected total cost on an order cycle is reduced substantially at around 20% with our proposed optimal inventory control policy. An extensive sensitivity analysis is conducted to generate additional insights. PMID:29527283

Inventory Control System for a Healthcare Apparel Service Centre with Stockout Risk: A Case Analysis.

PubMed

Pan, An; Hui, Chi-Leung

2017-01-01

Based on the real-world inventory control problem of a capacitated healthcare apparel service centre in Hong Kong which provides tailor-made apparel-making services for the elderly and disabled people, this paper studies a partial backordered continuous review inventory control problem in which the product demand follows a Poisson process with a constant lead time. The system is controlled by an ( Q , r ) inventory policy which incorporate the stockout risk, storage capacity, and partial backlog. The healthcare apparel service centre, under the capacity constraint, aims to minimize the inventory cost and achieving a low stockout risk. To address this challenge, an optimization problem is constructed. A real case-based data analysis is conducted, and the result shows that the expected total cost on an order cycle is reduced substantially at around 20% with our proposed optimal inventory control policy. An extensive sensitivity analysis is conducted to generate additional insights.

The effect of proximity to hurricanes Katrina and Rita on subsequent hurricane outlook and optimistic bias.

PubMed

Trumbo, Craig; Lueck, Michelle; Marlatt, Holly; Peek, Lori

2011-12-01

This study evaluated how individuals living on the Gulf Coast perceived hurricane risk after Hurricanes Katrina and Rita. It was hypothesized that hurricane outlook and optimistic bias for hurricane risk would be associated positively with distance from the Katrina-Rita landfall (more optimism at greater distance), controlling for historically based hurricane risk and county population density, demographics, individual hurricane experience, and dispositional optimism. Data were collected in January 2006 through a mail survey sent to 1,375 households in 41 counties on the coast (n = 824, 60% response). The analysis used hierarchal regression to test hypotheses. Hurricane history and population density had no effect on outlook; individuals who were male, older, and with higher household incomes were associated with lower risk perception; individual hurricane experience and personal impacts from Katrina and Rita predicted greater risk perception; greater dispositional optimism predicted more optimistic outlook; distance had a small effect but predicted less optimistic outlook at greater distance (model R(2) = 0.21). The model for optimistic bias had fewer effects: age and community tenure were significant; dispositional optimism had a positive effect on optimistic bias; distance variables were not significant (model R(2) = 0.05). The study shows that an existing measure of hurricane outlook has utility, hurricane outlook appears to be a unique concept from hurricane optimistic bias, and proximity has at most small effects. Future extension of this research will include improved conceptualization and measurement of hurricane risk perception and will bring to focus several concepts involving risk communication. © 2011 Society for Risk Analysis.

Globalization of pediatric transplantation: The risk of tuberculosis or not tuberculosis.

PubMed

McCulloch, Mignon; Lin, Philana Ling

2017-05-01

The risk of TB among pediatric SOT recipients increases as the globalization of medical care continues to broaden. Unlike adults, children and especially infants are more susceptible to TB as a complication after transplantation. Little data exist regarding the true incidence of TB and the optimal risk-based management of this very vulnerable population. Here, we highlight the theoretical and practical issues that complicate the management of these patients and pose some questions that should be addressed when managing these patients. More data are needed to provide optimal guidance of the best diagnostic and management practices to this unique population. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Integrated Medical Model - Optimizing In-flight Space Medical Systems to Reduce Crew Health Risk and Mission Impacts

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Walton, Marlei; Minard, Charles; Saile, Lynn; Myers, Jerry; Butler, Doug; Lyengar, Sriram; Fitts, Mary; Johnson-Throop, Kathy

2009-01-01

The Integrated Medical Model (IMM) is a decision support tool used by medical system planners and designers as they prepare for exploration planning activities of the Constellation program (CxP). IMM provides an evidence-based approach to help optimize the allocation of in-flight medical resources for a specified level of risk within spacecraft operational constraints. Eighty medical conditions and associated resources are represented in IMM. Nine conditions are due to Space Adaptation Syndrome. The IMM helps answer fundamental medical mission planning questions such as What medical conditions can be expected? What type and quantity of medical resources are most likely to be used?", and "What is the probability of crew death or evacuation due to medical events?" For a specified mission and crew profile, the IMM effectively characterizes the sequence of events that could potentially occur should a medical condition happen. The mathematical relationships among mission and crew attributes, medical conditions and incidence data, in-flight medical resources, potential clinical and crew health end states are established to generate end state probabilities. A Monte Carlo computational method is used to determine the probable outcomes and requires up to 25,000 mission trials to reach convergence. For each mission trial, the pharmaceuticals and supplies required to diagnose and treat prevalent medical conditions are tracked and decremented. The uncertainty of patient response to treatment is bounded via a best-case, worst-case, untreated case algorithm. A Crew Health Index (CHI) metric, developed to account for functional impairment due to a medical condition, provides a quantified measure of risk and enables risk comparisons across mission scenarios. The use of historical in-flight medical data, terrestrial surrogate data as appropriate, and space medicine subject matter expertise has enabled the development of a probabilistic, stochastic decision support tool capable of optimizing in-flight medical systems based on crew and mission parameters. This presentation will illustrate how to apply quantitative risk assessment methods to optimize the mass and volume of space-based medical systems for a space flight mission given the level of crew health and mission risk.

Validity and reliability of the Turkish version of the Optimality Index-US (OI-US) to assess maternity care outcomes.

PubMed

Yucel, Cigdem; Taskin, Lale; Low, Lisa Kane

2015-12-01

Although obstetrical interventions are used commonly in Turkey, there is no standardized evidence-based assessment tool to evaluate maternity care outcomes. The Optimality Index-US (OI-US) is an evidence-based tool that was developed for the purpose of measuring aggregate perinatal care processes and outcomes against an optimal or best possible standard. This index has been validated and used in Netherlands, USA and UK until now. The objective of this study was to adapt the OI-US to assess maternity care outcomes in Turkey. Translation and back translation were used to develop the Optimality Index-Turkey (OI-TR) version. To evaluate the content validity of the OI-TR, an expert panel group (n=10) reviewed the items and evidence-based quality of the OI-TR for application in Turkey. Following the content validity process, the OI-TR was used to assess 150 healthy and 150 high-risk pregnant women who gave birth at a high volume, urban maternity hospital in Turkey. The scores between the two groups were compared to assess the discriminant validity of the OI-TR. The percentage of agreement between two raters and the Kappa statistic were calculated to evaluate the reliability. Content validity was established for the OI-TR by an expert group. Discriminant validity was confirmed by comparing the OI scores of healthy pregnant women (mean OI score=77.65%) and those of high-risk pregnant women (mean OI score=78.60%). The percentage of agreement between the two raters was 96.19, and inter-rater agreement was provided for each item in the OI-TR. OI-TR is a valid and reliable tool that can be used to assess maternity care outcomes in Turkey. The results of this study indicate that although the risk statuses of the women differed, the type of care they received was essentially the same, as measured by the OI-TR. Care was not individualised based on risk and for a majority of items was inconsistent with evidence based practice, which is not optimal. Use of the OI-TR will help to provide a standardized way to assess maternity care process and outcomes of maternity care in Turkey which can inform future research aimed at improving maternity care outcomes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Applications of polynomial optimization in financial risk investment

NASA Astrophysics Data System (ADS)

Zeng, Meilan; Fu, Hongwei

2017-09-01

Recently, polynomial optimization has many important applications in optimization, financial economics and eigenvalues of tensor, etc. This paper studies the applications of polynomial optimization in financial risk investment. We consider the standard mean-variance risk measurement model and the mean-variance risk measurement model with transaction costs. We use Lasserre's hierarchy of semidefinite programming (SDP) relaxations to solve the specific cases. The results show that polynomial optimization is effective for some financial optimization problems.

Using genetic algorithm to solve a new multi-period stochastic optimization model

NASA Astrophysics Data System (ADS)

Zhang, Xin-Li; Zhang, Ke-Cun

2009-09-01

This paper presents a new asset allocation model based on the CVaR risk measure and transaction costs. Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [N. Hibiki, A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation, in: H. Takahashi, (Ed.) The Japanese Association of Financial Econometrics and Engineering, JAFFE Journal (2001) 89-119 (in Japanese); N. Hibiki A hybrid simulation/tree stochastic optimization model for dynamic asset allocation, in: B. Scherer (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, 2003, pp. 269-294], which was called a hybrid model. However, the transaction costs weren't considered in that paper. In this paper, we improve Hibiki's model in the following aspects: (1) The risk measure CVaR is introduced to control the wealth loss risk while maximizing the expected utility; (2) Typical market imperfections such as short sale constraints, proportional transaction costs are considered simultaneously. (3) Applying a genetic algorithm to solve the resulting model is discussed in detail. Numerical results show the suitability and feasibility of our methodology.

Shape optimization of pulsatile ventricular assist devices using FSI to minimize thrombotic risk

NASA Astrophysics Data System (ADS)

Long, C. C.; Marsden, A. L.; Bazilevs, Y.

2014-10-01

In this paper we perform shape optimization of a pediatric pulsatile ventricular assist device (PVAD). The device simulation is carried out using fluid-structure interaction (FSI) modeling techniques within a computational framework that combines FEM for fluid mechanics and isogeometric analysis for structural mechanics modeling. The PVAD FSI simulations are performed under realistic conditions (i.e., flow speeds, pressure levels, boundary conditions, etc.), and account for the interaction of air, blood, and a thin structural membrane separating the two fluid subdomains. The shape optimization study is designed to reduce thrombotic risk, a major clinical problem in PVADs. Thrombotic risk is quantified in terms of particle residence time in the device blood chamber. Methods to compute particle residence time in the context of moving spatial domains are presented in a companion paper published in the same issue (Comput Mech, doi: 10.1007/s00466-013-0931-y, 2013). The surrogate management framework, a derivative-free pattern search optimization method that relies on surrogates for increased efficiency, is employed in this work. For the optimization study shown here, particle residence time is used to define a suitable cost or objective function, while four adjustable design optimization parameters are used to define the device geometry. The FSI-based optimization framework is implemented in a parallel computing environment, and deployed with minimal user intervention. Using five SEARCH/ POLL steps the optimization scheme identifies a PVAD design with significantly better throughput efficiency than the original device.

Benefit of an electronic medical record-based alarm in the optimization of stress ulcer prophylaxis.

PubMed

Saad, Emanuel José; Bedini, Marianela; Becerra, Ana Florencia; Martini, Gustavo Daniel; Gonzalez, Jacqueline Griselda; Bolomo, Andrea; Castellani, Luciana; Quiroga, Silvana; Morales, Cristian; Leathers, James; Balderramo, Domingo; Albertini, Ricardo Arturo

2018-06-09

The use of stress ulcer prophylaxis (SUP) has risen in recent years, even in patients without a clear indication for therapy. To evaluate the efficacy of an electronic medical record (EMR)-based alarm to improve appropriate SUP use in hospitalized patients. We conducted an uncontrolled before-after study comparing SUP prescription in intensive care unit (ICU) patients and non-ICU patients, before and after the implementation of an EMR-based alarm that provided the correct indications for SUP. 1627 patients in the pre-intervention and 1513 patients in the post-intervention cohorts were included. The EMR-based alarm improved appropriate (49.6% vs. 66.6%, p<0.001) and reduced inappropriate SUP use (50.4% vs. 33.3%, p<0.001) in ICU patients only. These differences were related to the optimization of SUP in low risk patients. There was no difference in overt gastrointestinal bleeding between the two cohorts. Unjustified costs related to SUP were reduced by a third after EMR-based alarm use. The use of an EMR-based alarm improved appropriate and reduced inappropriate use of SUP in ICU patients. This benefit was limited to optimization in low risk patients and associated with a decrease in SUP costs. Copyright © 2018 Elsevier España, S.L.U. All rights reserved.

What's new in perioperative nutritional support?

PubMed

Awad, Sherif; Lobo, Dileep N

2011-06-01

To highlight recent developments in the field of perioperative nutritional support by reviewing clinically pertinent English language articles from October 2008 to December 2010, that examined the effects of malnutrition on surgical outcomes, optimizing metabolic function and nutritional status preoperatively and postoperatively. Recognition of patients with or at risk of malnutrition remains poor despite the availability of numerous clinical aids and clear evidence of the adverse effects of poor nutritional status on postoperative clinical outcomes. Unfortunately, poor design and significant heterogeneity remain amongst many studies of nutritional interventions in surgical patients. Patients undergoing elective surgery should be managed within a multimodal pathway that includes evidence-based interventions to optimize nutritional status perioperatively. The aforementioned should include screening patients to identify those at high nutritional risk, perioperative immuno-nutrition, minimizing 'metabolic stress' and insulin resistance by preoperative conditioning with carbohydrate-based drinks, glutamine supplementation, minimal access surgery and enhanced recovery protocols. Finally gut-specific nutrients and prokinetics should be utilized to improve enteral feed tolerance thereby permitting early enteral feeding. An evidence-based multimodal pathway that includes interventions to optimize nutritional status may improve outcomes following elective surgery.

A parallel optimization method for product configuration and supplier selection based on interval

NASA Astrophysics Data System (ADS)

Zheng, Jian; Zhang, Meng; Li, Guoxi

2017-06-01

In the process of design and manufacturing, product configuration is an important way of product development, and supplier selection is an essential component of supply chain management. To reduce the risk of procurement and maximize the profits of enterprises, this study proposes to combine the product configuration and supplier selection, and express the multiple uncertainties as interval numbers. An integrated optimization model of interval product configuration and supplier selection was established, and NSGA-II was put forward to locate the Pareto-optimal solutions to the interval multiobjective optimization model.

Role of the parameters involved in the plan optimization based on the generalized equivalent uniform dose and radiobiological implications

NASA Astrophysics Data System (ADS)

Widesott, L.; Strigari, L.; Pressello, M. C.; Benassi, M.; Landoni, V.

2008-03-01

We investigated the role and the weight of the parameters involved in the intensity modulated radiation therapy (IMRT) optimization based on the generalized equivalent uniform dose (gEUD) method, for prostate and head-and-neck plans. We systematically varied the parameters (gEUDmax and weight) involved in the gEUD-based optimization of rectal wall and parotid glands. We found that the proper value of weight factor, still guaranteeing planning treatment volumes coverage, produced similar organs at risks dose-volume (DV) histograms for different gEUDmax with fixed a = 1. Most of all, we formulated a simple relation that links the reference gEUDmax and the associated weight factor. As secondary objective, we evaluated plans obtained with the gEUD-based optimization and ones based on DV criteria, using the normal tissue complication probability (NTCP) models. gEUD criteria seemed to improve sparing of rectum and parotid glands with respect to DV-based optimization: the mean dose, the V40 and V50 values to the rectal wall were decreased of about 10%, the mean dose to parotids decreased of about 20-30%. But more than the OARs sparing, we underlined the halving of the OARs optimization time with the implementation of the gEUD-based cost function. Using NTCP models we enhanced differences between the two optimization criteria for parotid glands, but no for rectum wall.

Classification of individual well-being scores for the determination of adverse health and productivity outcomes in employee populations.

PubMed

Shi, Yuyan; Sears, Lindsay E; Coberley, Carter R; Pope, James E

2013-04-01

Adverse health and productivity outcomes have imposed a considerable economic burden on employers. To facilitate optimal worksite intervention designs tailored to differing employee risk levels, the authors established cutoff points for an Individual Well-Being Score (IWBS) based on a global measure of well-being. Cross-sectional associations between IWBS and adverse health and productivity outcomes, including high health care cost, emergency room visits, short-term disability days, absenteeism, presenteeism, low job performance ratings, and low intentions to stay with the employer, were studied in a sample of 11,702 employees from a large employer. Receiver operating characteristics curves were evaluated to detect a single optimal cutoff value of IWBS for predicting 2 or more adverse outcomes. More granular segmentation was achieved by computing relative risks of each adverse outcome from logistic regressions accounting for sociodemographic characteristics. Results showed strong and significant nonlinear associations between IWBS and health and productivity outcomes. An IWBS of 75 was found to be the optimal single cutoff point to discriminate 2 or more adverse outcomes. Logistic regression models found abrupt reductions of relative risk also clustered at IWBS cutoffs of 53, 66, and 88, in addition to 75, which segmented employees into high, high-medium, medium, low-medium, and low risk groups. To determine validity and generalizability, cutoff values were applied in a smaller employee population (N=1853) and confirmed significant differences between risk groups across health and productivity outcomes. The reported segmentation of IWBS into discrete cohorts based on risk of adverse health and productivity outcomes should facilitate well-being comparisons and worksite interventions.

Estimating vegetation dryness to optimize fire risk assessment with spot vegetation satellite data in savanna ecosystems

NASA Astrophysics Data System (ADS)

Verbesselt, J.; Somers, B.; Lhermitte, S.; van Aardt, J.; Jonckheere, I.; Coppin, P.

2005-10-01

The lack of information on vegetation dryness prior to the use of fire as a management tool often leads to a significant deterioration of the savanna ecosystem. This paper therefore evaluated the capacity of SPOT VEGETATION time-series to monitor the vegetation dryness (i.e., vegetation moisture content per vegetation amount) in order to optimize fire risk assessment in the savanna ecosystem of Kruger National Park in South Africa. The integrated Relative Vegetation Index approach (iRVI) to quantify the amount of herbaceous biomass at the end of the rain season and the Accumulated Relative Normalized Difference vegetation index decrement (ARND) related to vegetation moisture content were selected. The iRVI and ARND related to vegetation amount and moisture content, respectively, were combined in order to monitor vegetation dryness and optimize fire risk assessment in the savanna ecosystems. In situ fire activity data was used to evaluate the significance of the iRVI and ARND to monitor vegetation dryness for fire risk assessment. Results from the binary logistic regression analysis confirmed that the assessment of fire risk was optimized by integration of both the vegetation quantity (iRVI) and vegetation moisture content (ARND) as statistically significant explanatory variables. Consequently, the integrated use of both iRVI and ARND to monitor vegetation dryness provides a more suitable tool for fire management and suppression compared to other traditional satellite-based fire risk assessment methods, only related to vegetation moisture content.

A tool for efficient, model-independent management optimization under uncertainty

USGS Publications Warehouse

White, Jeremy; Fienen, Michael N.; Barlow, Paul M.; Welter, Dave E.

2018-01-01

To fill a need for risk-based environmental management optimization, we have developed PESTPP-OPT, a model-independent tool for resource management optimization under uncertainty. PESTPP-OPT solves a sequential linear programming (SLP) problem and also implements (optional) efficient, “on-the-fly” (without user intervention) first-order, second-moment (FOSM) uncertainty techniques to estimate model-derived constraint uncertainty. Combined with a user-specified risk value, the constraint uncertainty estimates are used to form chance-constraints for the SLP solution process, so that any optimal solution includes contributions from model input and observation uncertainty. In this way, a “single answer” that includes uncertainty is yielded from the modeling analysis. PESTPP-OPT uses the familiar PEST/PEST++ model interface protocols, which makes it widely applicable to many modeling analyses. The use of PESTPP-OPT is demonstrated with a synthetic, integrated surface-water/groundwater model. The function and implications of chance constraints for this synthetic model are discussed.

Worksite-based cardiovascular risk screening and management: a feasibility study.

PubMed

Padwal, Raj; Rashead, Mohammad; Snider, Jonathan; Morrin, Louise; Lehman, Agnes; Campbell, Norm Rc

2017-01-01

Established cardiovascular risk factors are highly prevalent and contribute substantially to cardiovascular morbidity and mortality because they remain uncontrolled in many Canadians. Worksite-based cardiovascular risk factor screening and management represent a largely untapped strategy for optimizing risk factor control. In a 2-phase collaborative demonstration project between Alberta Health Services (AHS) and the Alberta Newsprint Company (ANC), ANC employees were offered cardiovascular risk factor screening and management. Screening was performed at the worksite by AHS nurses, who collected baseline history, performed automated blood pressure measurement and point-of-care testing for lipids and A1c, and calculated 10-year Framingham risk. Employees with a Framingham risk score of ≥10% and uncontrolled blood pressure, dyslipidemia, or smoking were offered 6 months of pharmacist case management to optimize their risk factor control. In total, 87 of 190 (46%) employees volunteered to undergo cardiovascular risk factor screening. Mean age was 44.5±11.9 years, 73 (83.9%) were male, 14 (16.1%) had hypertension, 4 (4.6%) had diabetes, 12 (13.8%) were current smokers, and 9 (10%) had dyslipidemia. Of 36 employees with an estimated Framingham risk score of ≥10%, 21 (58%) agreed to receive case management and 15 (42%) attended baseline and 6-month follow-up case management visits. Statistically significant reductions in left arm systolic blood pressure (-8.0±12.4 mmHg; p =0.03) and triglyceride levels (-0.8±1.4 mmol/L; p =0.04) occurred following case management. These findings demonstrate the feasibility and usefulness of collaborative, worksite-based cardiovascular risk factor screening and management. Expansion of this type of partnership in a cost-effective manner is warranted.

Determining optimal gestational weight gain in a multiethnic Asian population.

PubMed

Ee, Tat Xin; Allen, John Carson; Malhotra, Rahul; Koh, Huishan; Østbye, Truls; Tan, Thiam Chye

2014-04-01

To define the optimal gestational weight gain (GWG) for the multiethnic Singaporean population. Data from 1529 live singleton deliveries was analyzed. A multinomial logistic regression analysis, with GWG as the predictor, was conducted to determine the lowest aggregated risk of a composite perinatal outcome, stratified by Asia-specific body mass index (BMI) categories. The composite perinatal outcome, based on a combination of delivery type (cesarean section [CS], vaginal delivery [VD]) and size for gestational age (small [SGA], appropriate [AGA], large [LGA]), had six categories: (i) VD with LGA; (ii) VD with SGA; (iii) CS with AGA; (iv) CS with SGA; (v) CS with LGA; (vi) and VD with AGA. The last was considered as the 'normal' reference category. In each BMI category, the GWG value corresponding to the lowest aggregated risk was defined as the optimal GWG, and the GWG values at which the aggregated risk did not exceed a 5% increase from the lowest aggregated risk were defined as the margins of the optimal GWG range. The optimal GWG by pre-pregnancy BMI category, was 19.5 kg (range, 12.9 to 23.9) for underweight, 13.7 kg (7.7 to 18.8) for normal weight, 7.9 kg (2.6 to 14.0) for overweight and 1.8 kg (-5.0 to 7.0) for obese. The results of this study, the first to determine optimal GWG in the multiethnic Singaporean population, concur with the Institute of Medicine (IOM) guidelines in that GWG among Asian women who are heavier prior to pregnancy, especially those who are obese, should be lower. However, the optimal GWG for underweight and obese women was outside the IOM recommended range. © 2014 The Authors. Journal of Obstetrics and Gynaecology Research © 2014 Japan Society of Obstetrics and Gynecology.

Optimal structural design of the midship of a VLCC based on the strategy integrating SVM and GA

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2012-03-01

In this paper a hybrid process of modeling and optimization, which integrates a support vector machine (SVM) and genetic algorithm (GA), was introduced to reduce the high time cost in structural optimization of ships. SVM, which is rooted in statistical learning theory and an approximate implementation of the method of structural risk minimization, can provide a good generalization performance in metamodeling the input-output relationship of real problems and consequently cuts down on high time cost in the analysis of real problems, such as FEM analysis. The GA, as a powerful optimization technique, possesses remarkable advantages for the problems that can hardly be optimized with common gradient-based optimization methods, which makes it suitable for optimizing models built by SVM. Based on the SVM-GA strategy, optimization of structural scantlings in the midship of a very large crude carrier (VLCC) ship was carried out according to the direct strength assessment method in common structural rules (CSR), which eventually demonstrates the high efficiency of SVM-GA in optimizing the ship structural scantlings under heavy computational complexity. The time cost of this optimization with SVM-GA has been sharply reduced, many more loops have been processed within a small amount of time and the design has been improved remarkably.

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems

PubMed Central

Yu, Hao; Solvang, Wei Deng

2016-01-01

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment. PMID:27258293

A new perspective on optimal care for patients with COPD.

PubMed

Postma, Dirkje; Anzueto, Antonio; Calverley, Peter; Jenkins, Christine; Make, Barry J; Sciurba, Frank C; Similowski, Thomas; van der Molen, Thys; Eriksson, Göran

2011-06-01

Worldwide, clinicians face the task of providing millions of patients with the best possible treatment and management of COPD. Currently, management primarily involves short-term 'here-and-now' goals, targeting immediate patient benefit. However, although there is considerable knowledge available to assist clinicians in minimising the current impact of COPD on patients, relatively little is known about which dominant factors predict future risks. These predictors may vary for different outcomes, such as exacerbations, mortality, co-morbidities, and the long-term consequences of COPD. We propose a new paradigm to achieve 'optimal COPD care' based on the concept that here-and-now goals should be integrated with goals to improve long-term outcomes and reduce future risks. Whilst knowledge on risk factors for poorer outcomes in COPD is growing and some data exist on positive effects of pharmacological interventions, information on defining the benefits of all commonly used interventions for reducing the risk of various future disease outcomes is still scarce. Greater insight is needed into the relationships between the two pillars of optimal COPD care: 'best current control' and 'future risk reduction'. This broader approach to disease management should result in improved care for every COPD patient now and into the future.

An Improved Multi-Objective Programming with Augmented ε-Constraint Method for Hazardous Waste Location-Routing Problems.

PubMed

Yu, Hao; Solvang, Wei Deng

2016-05-31

Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.

Maintenance service contract model for heavy equipment in mining industry using principal agent theory

NASA Astrophysics Data System (ADS)

Pakpahan, Eka K. A.; Iskandar, Bermawi P.

2015-12-01

Mining industry is characterized by a high operational revenue, and hence high availability of heavy equipment used in mining industry is a critical factor to ensure the revenue target. To maintain high avaliability of the heavy equipment, the equipment's owner hires an agent to perform maintenance action. Contract is then used to control the relationship between the two parties involved. The traditional contracts such as fixed price, cost plus or penalty based contract studied is unable to push agent's performance to exceed target, and this in turn would lead to a sub-optimal result (revenue). This research deals with designing maintenance contract compensation schemes. The scheme should induce agent to select the highest possible maintenance effort level, thereby pushing agent's performance and achieve maximum utility for both parties involved. Principal agent theory is used as a modeling approach due to its ability to simultaneously modeled owner and agent decision making process. Compensation schemes considered in this research includes fixed price, cost sharing and revenue sharing. The optimal decision is obtained using a numerical method. The results show that if both parties are risk neutral, then there are infinite combination of fixed price, cost sharing and revenue sharing produced the same optimal solution. The combination of fixed price and cost sharing contract results in the optimal solution when the agent is risk averse, while the optimal combination of fixed price and revenue sharing contract is obtained when agent is risk averse. When both parties are risk averse, the optimal compensation scheme is a combination of fixed price, cost sharing and revenue sharing.

Managing simulation-based training: A framework for optimizing learning, cost, and time

NASA Astrophysics Data System (ADS)

Richmond, Noah Joseph

This study provides a management framework for optimizing training programs for learning, cost, and time when using simulation based training (SBT) and reality based training (RBT) as resources. Simulation is shown to be an effective means for implementing activity substitution as a way to reduce risk. The risk profile of 22 US Air Force vehicles are calculated, and the potential risk reduction is calculated under the assumption of perfect substitutability of RBT and SBT. Methods are subsequently developed to relax the assumption of perfect substitutability. The transfer effectiveness ratio (TER) concept is defined and modeled as a function of the quality of the simulator used, and the requirements of the activity trained. The Navy F/A-18 is then analyzed in a case study illustrating how learning can be maximized subject to constraints in cost and time, and also subject to the decision maker's preferences for the proportional and absolute use of simulation. Solution methods for optimizing multiple activities across shared resources are next provided. Finally, a simulation strategy including an operations planning program (OPP), an implementation program (IP), an acquisition program (AP), and a pedagogical research program (PRP) is detailed. The study provides the theoretical tools to understand how to leverage SBT, a case study demonstrating these tools' efficacy, and a set of policy recommendations to enable the US military to better utilize SBT in the future.

The HTA Risk Analysis Chart: Visualising the Need for and Potential Value of Managed Entry Agreements in Health Technology Assessment.

PubMed

Grimm, Sabine Elisabeth; Strong, Mark; Brennan, Alan; Wailoo, Allan J

2017-12-01

Recent changes to the regulatory landscape of pharmaceuticals may sometimes require reimbursement authorities to issue guidance on technologies that have a less mature evidence base. Decision makers need to be aware of risks associated with such health technology assessment (HTA) decisions and the potential to manage this risk through managed entry agreements (MEAs). This work develops methods for quantifying risk associated with specific MEAs and for clearly communicating this to decision makers. We develop the 'HTA risk analysis chart', in which we present the payer strategy and uncertainty burden (P-SUB) as a measure of overall risk. The P-SUB consists of the payer uncertainty burden (PUB), the risk stemming from decision uncertainty as to which is the truly optimal technology from the relevant set of technologies, and the payer strategy burden (PSB), the additional risk of approving a technology that is not expected to be optimal. We demonstrate the approach using three recent technology appraisals from the UK National Institute for Health and Clinical Excellence (NICE), each of which considered a price-based MEA. The HTA risk analysis chart was calculated using results from standard probabilistic sensitivity analyses. In all three HTAs, the new interventions were associated with substantial risk as measured by the P-SUB. For one of these technologies, the P-SUB was reduced to zero with the proposed price reduction, making this intervention cost effective with near complete certainty. For the other two, the risk reduced substantially with a much reduced PSB and a slightly increased PUB. The HTA risk analysis chart shows the risk that the healthcare payer incurs under unresolved decision uncertainty and when considering recommending a technology that is not expected to be optimal given current evidence. This allows the simultaneous consideration of financial and data-collection MEA schemes in an easily understood format. The use of HTA risk analysis charts will help to ensure that MEAs are considered within a standard utility-maximising health economic decision-making framework.

Optimal linear and nonlinear feature extraction based on the minimization of the increased risk of misclassification. [Bayes theorem - statistical analysis/data processing

NASA Technical Reports Server (NTRS)

Defigueiredo, R. J. P.

1974-01-01

General classes of nonlinear and linear transformations were investigated for the reduction of the dimensionality of the classification (feature) space so that, for a prescribed dimension m of this space, the increase of the misclassification risk is minimized.

Value-based formulas for purchasing. PEHP's designated service provider program: value-based purchasing through global fees.

PubMed

Emery, D W

1997-01-01

In many circles, managed care and capitation have become synonymous; unfortunately, the assumptions informing capitation are based on a flawed unidimensional model of risk. PEHP of Utah has rejected the unidimensional model and has therefore embraced a multidimensional model of risk that suggests that global fees are the optimal purchasing modality. A globally priced episode of care forms a natural unit of analysis that enhances purchasing clarity, allows providers to more efficiently focus on the Marginal Rate of Technical Substitution, and conforms to the multidimensional reality of risk. Most importantly, global fees simultaneously maximize patient choice and provider cost consciousness.

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghomi, Pooyan Shirvani; Zinchenko, Yuriy

2014-08-15

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization softwaremore » Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.« less

A new methodology for surcharge risk management in urban areas (case study: Gonbad-e-Kavus city).

PubMed

Hooshyaripor, Farhad; Yazdi, Jafar

2017-02-01

This research presents a simulation-optimization model for urban flood mitigation integrating Non-dominated Sorting Genetic Algorithm (NSGA-II) with Storm Water Management Model (SWMM) hydraulic model under a curve number-based hydrologic model of low impact development technologies in Gonbad-e-Kavus, a small city in the north of Iran. In the developed model, the best performance of the system relies on the optimal layout and capacity of retention ponds over the study area in order to reduce surcharge from the manholes underlying a set of storm event loads, while the available investment plays a restricting role. Thus, there is a multi-objective optimization problem with two conflicting objectives solved successfully by NSGA-II to find a set of optimal solutions known as the Pareto front. In order to analyze the results, a new factor, investment priority index (IPI), is defined which shows the risk of surcharging over the network and priority of the mitigation actions. The IPI is calculated using the probability of pond selection for candidate locations and average depth of the ponds in all Pareto front solutions. The IPI can help the decision makers to arrange a long-term progressive plan with the priority of high-risk areas when an optimal solution has been selected.

The Research on Safety Management Information System of Railway Passenger Based on Risk Management Theory

NASA Astrophysics Data System (ADS)

Zhu, Wenmin; Jia, Yuanhua

2018-01-01

Based on the risk management theory and the PDCA cycle model, requirements of the railway passenger transport safety production is analyzed, and the establishment of the security risk assessment team is proposed to manage risk by FTA with Delphi from both qualitative and quantitative aspects. The safety production committee is also established to accomplish performance appraisal, which is for further ensuring the correctness of risk management results, optimizing the safety management business processes and improving risk management capabilities. The basic framework and risk information database of risk management information system of railway passenger transport safety are designed by Ajax, Web Services and SQL technologies. The system realizes functions about risk management, performance appraisal and data management, and provides an efficient and convenient information management platform for railway passenger safety manager.

Maximizing and minimizing investment concentration with constraints of budget and investment risk

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2018-01-01

In this paper, as a first step in examining the properties of a feasible portfolio subset that is characterized by budget and risk constraints, we assess the maximum and minimum of the investment concentration using replica analysis. To do this, we apply an analytical approach of statistical mechanics. We note that the optimization problem considered in this paper is the dual problem of the portfolio optimization problem discussed in the literature, and we verify that these optimal solutions are also dual. We also present numerical experiments, in which we use the method of steepest descent that is based on Lagrange's method of undetermined multipliers, and we compare the numerical results to those obtained by replica analysis in order to assess the effectiveness of our proposed approach.

Network Security Risk Assessment System Based on Attack Graph and Markov Chain

NASA Astrophysics Data System (ADS)

Sun, Fuxiong; Pi, Juntao; Lv, Jin; Cao, Tian

2017-10-01

Network security risk assessment technology can be found in advance of the network problems and related vulnerabilities, it has become an important means to solve the problem of network security. Based on attack graph and Markov chain, this paper provides a Network Security Risk Assessment Model (NSRAM). Based on the network infiltration tests, NSRAM generates the attack graph by the breadth traversal algorithm. Combines with the international standard CVSS, the attack probability of atomic nodes are counted, and then the attack transition probabilities of ones are calculated by Markov chain. NSRAM selects the optimal attack path after comprehensive measurement to assessment network security risk. The simulation results show that NSRAM can reflect the actual situation of network security objectively.

Combining transrectal ultrasound and CT for image-guided adaptive brachytherapy of cervical cancer: Proof of concept.

PubMed

Nesvacil, Nicole; Schmid, Maximilian P; Pötter, Richard; Kronreif, Gernot; Kirisits, Christian

To investigate the feasibility of a treatment planning workflow for three-dimensional image-guided cervix cancer brachytherapy, combining volumetric transrectal ultrasound (TRUS) for target definition with CT for dose optimization to organs at risk (OARs), for settings with no access to MRI. A workflow for TRUS/CT-based volumetric treatment planning was developed, based on a customized system including ultrasound probe, stepper unit, and software for image volume acquisition. A full TRUS/CT-based workflow was simulated in a clinical case and compared with MR- or CT-only delineation. High-risk clinical target volume was delineated on TRUS, and OARs were delineated on CT. Manually defined tandem/ring applicator positions on TRUS and CT were used as a reference for rigid registration of the image volumes. Treatment plan optimization for TRUS target and CT organ volumes was performed and compared to MRI and CT target contours. TRUS/CT-based contouring, applicator reconstruction, image fusion, and treatment planning were feasible, and the full workflow could be successfully demonstrated. The TRUS/CT plan fulfilled all clinical planning aims. Dose-volume histogram evaluation of the TRUS/CT-optimized plan (high-risk clinical target volume D 90 , OARs D 2cm³ for) on different image modalities showed good agreement between dose values reported for TRUS/CT and MRI-only reference contours and large deviations for CT-only target parameters. A TRUS/CT-based workflow for full three-dimensional image-guided cervix brachytherapy treatment planning seems feasible and may be clinically comparable to MRI-based treatment planning. Further development to solve challenges with applicator definition in the TRUS volume is required before systematic applicability of this workflow. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Optimizing Processes to Minimize Risk

NASA Technical Reports Server (NTRS)

Loyd, David

2017-01-01

NASA, like the other hazardous industries, has suffered very catastrophic losses. Human error will likely never be completely eliminated as a factor in our failures. When you can't eliminate risk, focus on mitigating the worst consequences and recovering operations. Bolstering processes to emphasize the role of integration and problem solving is key to success. Building an effective Safety Culture bolsters skill-based performance that minimizes risk and encourages successful engagement.

Stochastic optimization algorithms for barrier dividend strategies

NASA Astrophysics Data System (ADS)

Yin, G.; Song, Q. S.; Yang, H.

2009-01-01

This work focuses on finding optimal barrier policy for an insurance risk model when the dividends are paid to the share holders according to a barrier strategy. A new approach based on stochastic optimization methods is developed. Compared with the existing results in the literature, more general surplus processes are considered. Precise models of the surplus need not be known; only noise-corrupted observations of the dividends are used. Using barrier-type strategies, a class of stochastic optimization algorithms are developed. Convergence of the algorithm is analyzed; rate of convergence is also provided. Numerical results are reported to demonstrate the performance of the algorithm.

Insurance principles and the design of prospective payment systems.

PubMed

Ellis, R P; McGuire, T G

1988-09-01

This paper applies insurance principles to the issues of optimal outlier payments and designation of peer groups in Medicare's case-based prospective payment system for hospital care. Arrow's principle that full insurance after a deductible is optimal implies that, to minimize hospital risk, outlier payments should be based on hospital average loss per case rather than, as at present, based on individual case-level losses. The principle of experience rating implies defining more homogenous peer groups for the purpose of figuring average cost. The empirical significance of these results is examined using a sample of 470,568 discharges from 469 hospitals.

Classification of Individual Well-Being Scores for the Determination of Adverse Health and Productivity Outcomes in Employee Populations

PubMed Central

Sears, Lindsay E.; Coberley, Carter R.; Pope, James E.

2013-01-01

Abstract Adverse health and productivity outcomes have imposed a considerable economic burden on employers. To facilitate optimal worksite intervention designs tailored to differing employee risk levels, the authors established cutoff points for an Individual Well-Being Score (IWBS) based on a global measure of well-being. Cross-sectional associations between IWBS and adverse health and productivity outcomes, including high health care cost, emergency room visits, short-term disability days, absenteeism, presenteeism, low job performance ratings, and low intentions to stay with the employer, were studied in a sample of 11,702 employees from a large employer. Receiver operating characteristics curves were evaluated to detect a single optimal cutoff value of IWBS for predicting 2 or more adverse outcomes. More granular segmentation was achieved by computing relative risks of each adverse outcome from logistic regressions accounting for sociodemographic characteristics. Results showed strong and significant nonlinear associations between IWBS and health and productivity outcomes. An IWBS of 75 was found to be the optimal single cutoff point to discriminate 2 or more adverse outcomes. Logistic regression models found abrupt reductions of relative risk also clustered at IWBS cutoffs of 53, 66, and 88, in addition to 75, which segmented employees into high, high-medium, medium, low-medium, and low risk groups. To determine validity and generalizability, cutoff values were applied in a smaller employee population (N=1853) and confirmed significant differences between risk groups across health and productivity outcomes. The reported segmentation of IWBS into discrete cohorts based on risk of adverse health and productivity outcomes should facilitate well-being comparisons and worksite interventions. (Population Health Management 2013;16:90–98) PMID:23013034

Efficient discovery of risk patterns in medical data.

PubMed

Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

2009-01-01

This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

Dispositional optimism and perceived risk interact to predict intentions to learn genome sequencing results.

PubMed

Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B

2015-07-01

Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. (c) 2015 APA, all rights reserved.

Dispositional Optimism and Perceived Risk Interact to Predict Intentions to Learn Genome Sequencing Results

PubMed Central

Taber, Jennifer M.; Klein, William M. P.; Ferrer, Rebecca A.; Lewis, Katie L.; Biesecker, Leslie G.; Biesecker, Barbara B.

2015-01-01

Objective Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Method Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Results Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. Conclusions The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. PMID:25313897

Spectral risk measures: the risk quadrangle and optimal approximation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kouri, Drew P.

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. Lastly, we prove the consistency of this approximation and demonstrate our results through numerical examples.

Spectral risk measures: the risk quadrangle and optimal approximation

DOE PAGES

Kouri, Drew P.

2018-05-24

We develop a general risk quadrangle that gives rise to a large class of spectral risk measures. The statistic of this new risk quadrangle is the average value-at-risk at a specific confidence level. As such, this risk quadrangle generates a continuum of error measures that can be used for superquantile regression. For risk-averse optimization, we introduce an optimal approximation of spectral risk measures using quadrature. Lastly, we prove the consistency of this approximation and demonstrate our results through numerical examples.

Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method

PubMed Central

Zhang, Wei; Wei, Shilin; Teng, Yanbin; Zhang, Jianku; Wang, Xiufang; Yan, Zheping

2017-01-01

In view of a dynamic obstacle environment with motion uncertainty, we present a dynamic collision avoidance method based on the collision risk assessment and improved velocity obstacle method. First, through the fusion optimization of forward-looking sonar data, the redundancy of the data is reduced and the position, size and velocity information of the obstacles are obtained, which can provide an accurate decision-making basis for next-step collision avoidance. Second, according to minimum meeting time and the minimum distance between the obstacle and unmanned underwater vehicle (UUV), this paper establishes the collision risk assessment model, and screens key obstacles to avoid collision. Finally, the optimization objective function is established based on the improved velocity obstacle method, and a UUV motion characteristic is used to calculate the reachable velocity sets. The optimal collision speed of UUV is searched in velocity space. The corresponding heading and speed commands are calculated, and outputted to the motion control module. The above is the complete dynamic obstacle avoidance process. The simulation results show that the proposed method can obtain a better collision avoidance effect in the dynamic environment, and has good adaptability to the unknown dynamic environment. PMID:29186878

Stratification strategy for evaluating the influence of diabetes complication severity index on the risk of hospitalization: a record linkage data in Western Australia.

PubMed

Ha, Ninh Thi; Harris, Mark; Robinson, Suzanne; Preen, David; Moorin, Rachael

2017-07-01

This study aimed to develop a risk stratification strategy for evaluating the relationship between complications of diabetes and the risk of diabetic-related hospitalization to accurately classify diabetes severity. The study used administrative health records for 40,624 individuals with diabetes aged ≥18years in Western Australian. The adapted Diabetes Complication Severity Index (DCSI), socio-demographic and clinical characteristics were used in random effects negative binomial and threshold effect models to determine the optimal stratification strategy for diabetes severity based on the homogeneity of the risk of hospitalization in response to variation of the DCSI. The optimal stratification of people with diabetes was specified by four sub-populations. The first sub-population was no complications with an inverse association with the risk of hospitalizations (coefficient-0.247, SE 0.03). Further three sub-populations with DCSI at one (coefficient 0.289, SE 0.01), two (coefficient 0.339, SE 0.01) and three or more (coefficient 0.381, SE 0.01) were used to accurately describe the impact of DCSI on the risk of hospitalization. A stratification into four subpopulations based on the homogeneous impact of diabetes DCSI on the risk of hospitalization may be more suitable for evaluating health care interventions and planning health care provision. Copyright © 2017 Elsevier Inc. All rights reserved.

Fetal and Postnatal Head Circumference Growth: Synergetic Factors for Neurodevelopmental Outcome at 2 Years of Age for Preterm Infants.

PubMed

Sicard, Mélanie; Nusinovici, Simon; Hanf, Matthieu; Muller, Jean-Baptiste; Guellec, Isabelle; Ancel, Pierre-Yves; Gascoin, Géraldine; Rozé, Jean-Christophe; Flamant, Cyril

2017-01-01

Preterm infants present higher risk of non-optimal neurodevelopmental outcome. Fetal and postnatal growth, in particular head circumference (HC), is associated with neurodevelopmental outcome. We aimed to calculate the relationship between HC at birth, HC delta Z-score (between birth and hospital discharge), and non-optimal neurodevelopmental outcome at 2 years of corrected age in preterm infants. Surviving infants born ≤34 weeks of gestation were included in the analysis. The relationship between the risk of being non-optimal at 2 years and both HC at birth and HC growth was assessed. The 2 Z-scores were considered first independently and then simultaneously to investigate their effect on the risk of non-optimality using a generalized additive model. A total of 4,046 infants with both HC measures at birth and hospital discharge were included. Infants with small HC at birth (Z-score <-2 SD), or presenting suboptimal HC growth (dZ-score <-2 SD), are at higher risk of non-optimal neurodevelopmental outcome at 2 years (respectively OR 1.7 [95% CI 1.4-2] and OR 1.4 [95% CI 1.2-1.8]). Interestingly, patients cumulating small HC Z-score at birth (-2 SD) and presenting catch-down growth (HC dZ-score [-2 SD]) have a significantly increased risk for neurocognitive impairment (OR >2) while adjusting for gestational age, twin status, sex, and socioeconomic information. HC at birth and HC dZ-score between birth and hospital discharge are synergistically associated to neurodevelopmental outcome at 2 years of corrected age, in a population-based prospective cohort of preterm infants born ≤34 weeks of gestation. © 2017 S. Karger AG, Basel.

Study of a risk-based piping inspection guideline system.

PubMed

Tien, Shiaw-Wen; Hwang, Wen-Tsung; Tsai, Chih-Hung

2007-02-01

A risk-based inspection system and a piping inspection guideline model were developed in this study. The research procedure consists of two parts--the building of a risk-based inspection model for piping and the construction of a risk-based piping inspection guideline model. Field visits at the plant were conducted to develop the risk-based inspection and strategic analysis system. A knowledge-based model had been built in accordance with international standards and local government regulations, and the rational unified process was applied for reducing the discrepancy in the development of the models. The models had been designed to analyze damage factors, damage models, and potential damage positions of piping in the petrochemical plants. The purpose of this study was to provide inspection-related personnel with the optimal planning tools for piping inspections, hence, to enable effective predictions of potential piping risks and to enhance the better degree of safety in plant operations that the petrochemical industries can be expected to achieve. A risk analysis was conducted on the piping system of a petrochemical plant. The outcome indicated that most of the risks resulted from a small number of pipelines.

Not Getting Burned: The Importance of Fire

Treesearch

Gregory S. Amacher; Arun S. Malik; Robert G. Haight

2005-01-01

We extend existing stand-level models of forest landowner behavior in the presence of fire risk to include the level and timing of fuel management activities. These activities reduce losses if a stand ignites. Based on simulations, we find the standard result that fire risk reduces the optimal rotation age does not hold when landowners use fuel management. Instead,...

Priority of a Hesitant Fuzzy Linguistic Preference Relation with a Normal Distribution in Meteorological Disaster Risk Assessment.

PubMed

Wang, Lihong; Gong, Zaiwu

2017-10-10

As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In some complex and non-procedural meteorological disaster risk assessments, a hesitant fuzzy linguistic preference relation (HFLPR) is often used to deal with a situation in which experts may be hesitant while providing preference information of a pairwise comparison of alternatives, that is, the degree of preference of one alternative over another. This study explores hesitation from the perspective of statistical distributions, and obtains an optimal ranking of an HFLPR based on chance-restricted programming, which provides a new approach for hesitant fuzzy optimisation of decision-making in meteorological disaster risk assessments.

Adoption and implementation of a computer-delivered HIV/STD risk-reduction intervention for African American adolescent females seeking services at county health departments: implementation optimization is urgently needed.

PubMed

DiClemente, Ralph J; Bradley, Erin; Davis, Teaniese L; Brown, Jennifer L; Ukuku, Mary; Sales, Jessica M; Rose, Eve S; Wingood, Gina M

2013-06-01

Although group-delivered HIV/sexually transmitted disease (STD) risk-reduction interventions for African American adolescent females have proven efficacious, they require significant financial and staffing resources to implement and may not be feasible in personnel- and resource-constrained public health clinics. We conducted a study assessing adoption and implementation of an evidence-based HIV/STD risk-reduction intervention that was translated from a group-delivered modality to a computer-delivered modality to facilitate use in county public health departments. Usage of the computer-delivered intervention was low across 8 participating public health clinics. Further investigation is needed to optimize implementation by identifying, understanding, and surmounting barriers that hamper timely and efficient implementation of technology-delivered HIV/STD risk-reduction interventions in county public health clinics.

Decision-theoretic methodology for reliability and risk allocation in nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.

1985-01-01

This paper describes a methodology for allocating reliability and risk to various reactor systems, subsystems, components, operations, and structures in a consistent manner, based on a set of global safety criteria which are not rigid. The problem is formulated as a multiattribute decision analysis paradigm; the multiobjective optimization, which is performed on a PRA model and reliability cost functions, serves as the guiding principle for reliability and risk allocation. The concept of noninferiority is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The assessment of the decision maker's preferencesmore » could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided and several outstanding issues such as generic allocation and preference assessment are discussed.« less

Adoption and Implementation of a Computer-delivered HIV/STD Risk-Reduction Intervention for African American Adolescent Females Seeking Services at County Health Departments: Implementation Optimization is Urgently Needed

PubMed Central

DiClemente, Ralph J.; Bradley, Erin; Davis, Teaniese L.; Brown, Jennifer L.; Ukuku, Mary; Sales, Jessica M.; Rose, Eve S.; Wingood, Gina M.

2013-01-01

Although group-delivered HIV/STD risk-reduction interventions for African American adolescent females have proven efficacious, they require significant financial and staffing resources to implement and may not be feasible in personnel- and resource-constrained public health clinics. We conducted a study assessing adoption and implementation of an evidence-based HIV/STD risk-reduction intervention that was translated from a group-delivered modality to a computer-delivered modality to facilitate use in county public health departments. Usage of the computer-delivered intervention was low across eight participating public health clinics. Further investigation is needed to optimize implementation by identifying, understanding and surmounting barriers that hamper timely and efficient implementation of technology-delivered HIV/STD risk-reduction interventions in county public health clinics. PMID:23673891

Optimization of vehicle deceleration to reduce occupant injury risks in frontal impact.

PubMed

Mizuno, Koji; Itakura, Takuya; Hirabayashi, Satoko; Tanaka, Eiichi; Ito, Daisuke

2014-01-01

In vehicle frontal impacts, vehicle acceleration has a large effect on occupant loadings and injury risks. In this research, an optimal vehicle crash pulse was determined systematically to reduce injury measures of rear seat occupants by using mathematical simulations. The vehicle crash pulse was optimized based on a vehicle deceleration-deformation diagram under the conditions that the initial velocity and the maximum vehicle deformation were constant. Initially, a spring-mass model was used to understand the fundamental parameters for optimization. In order to investigate the optimization under a more realistic situation, the vehicle crash pulse was also optimized using a multibody model of a Hybrid III dummy seated in the rear seat for the objective functions of chest acceleration and chest deflection. A sled test using a Hybrid III dummy was carried out to confirm the simulation results. Finally, the optimal crash pulses determined from the multibody simulation were applied to a human finite element (FE) model. The optimized crash pulse to minimize the occupant deceleration had a concave shape: a high deceleration in the initial phase, low in the middle phase, and high again in the final phase. This crash pulse shape depended on the occupant restraint stiffness. The optimized crash pulse determined from the multibody simulation was comparable to that from the spring-mass model. From the sled test, it was demonstrated that the optimized crash pulse was effective for the reduction of chest acceleration. The crash pulse was also optimized for the objective function of chest deflection. The optimized crash pulse in the final phase was lower than that obtained for the minimization of chest acceleration. In the FE analysis of the human FE model, the optimized pulse for the objective function of the Hybrid III chest deflection was effective in reducing rib fracture risks. The optimized crash pulse has a concave shape and is dependent on the occupant restraint stiffness and maximum vehicle deformation. The shapes of the optimized crash pulse in the final phase were different for the objective functions of chest acceleration and chest deflection due to the inertial forces of the head and upper extremities. From the human FE model analysis it was found that the optimized crash pulse for the Hybrid III chest deflection can substantially reduce the risk of rib cage fractures. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Hirt, Evelyn H.; Veeramany, Arun

This research report summaries the development and evaluation of a prototypic enhanced risk monitor (ERM) methodology (framework) that includes alternative risk metrics and uncertainty analysis. This updated ERM methodology accounts for uncertainty in the equipment condition assessment (ECA), the prognostic result, and the probabilistic risk assessment (PRA) model. It is anticipated that the ability to characterize uncertainty in the estimated risk and update the risk estimates in real time based on equipment condition assessment (ECA) will provide a mechanism for optimizing plant performance while staying within specified safety margins. These results (based on impacting active component O&M using real-time equipmentmore » condition information) are a step towards ERMs that, if integrated with AR supervisory plant control systems, can help control O&M costs and improve affordability of advanced reactors.« less

Optimal trading from minimizing the period of bankruptcy risk

NASA Astrophysics Data System (ADS)

Liehr, S.; Pawelzik, K.

2001-04-01

Assuming that financial markets behave similar to random walk processes we derive a trading strategy with variable investment which is based on the equivalence of the period of bankruptcy risk and the risk to profit ratio. We define a state dependent predictability measure which can be attributed to the deterministic and stochastic components of the price dynamics. The influence of predictability variations and especially of short term inefficiency structures on the optimal amount of investment is analyzed in the given context and a method for adaptation of a trading system to the proposed objective function is presented. Finally we show the performance of our trading strategy on the DAX and S&P 500 as examples for real world data using different types of prediction models in comparison.

Estimating risk of foreign exchange portfolio: Using VaR and CVaR based on GARCH-EVT-Copula model

NASA Astrophysics Data System (ADS)

Wang, Zong-Run; Chen, Xiao-Hong; Jin, Yan-Bo; Zhou, Yan-Ju

2010-11-01

This paper introduces GARCH-EVT-Copula model and applies it to study the risk of foreign exchange portfolio. Multivariate Copulas, including Gaussian, t and Clayton ones, were used to describe a portfolio risk structure, and to extend the analysis from a bivariate to an n-dimensional asset allocation problem. We apply this methodology to study the returns of a portfolio of four major foreign currencies in China, including USD, EUR, JPY and HKD. Our results suggest that the optimal investment allocations are similar across different Copulas and confidence levels. In addition, we find that the optimal investment concentrates on the USD investment. Generally speaking, t Copula and Clayton Copula better portray the correlation structure of multiple assets than Normal Copula.

Applying machine learning to pattern analysis for automated in-design layout optimization

NASA Astrophysics Data System (ADS)

Cain, Jason P.; Fakhry, Moutaz; Pathak, Piyush; Sweis, Jason; Gennari, Frank; Lai, Ya-Chieh

2018-04-01

Building on previous work for cataloging unique topological patterns in an integrated circuit physical design, a new process is defined in which a risk scoring methodology is used to rank patterns based on manufacturing risk. Patterns with high risk are then mapped to functionally equivalent patterns with lower risk. The higher risk patterns are then replaced in the design with their lower risk equivalents. The pattern selection and replacement is fully automated and suitable for use for full-chip designs. Results from 14nm product designs show that the approach can identify and replace risk patterns with quantifiable positive impact on the risk score distribution after replacement.

[Optimal versus maximal safety of the blood transfusion chain in The Netherlands; results of a conference. College for Blood Transfusion of the Dutch Red Cross].

PubMed

van der Poel, C L; de Boer, J E; Reesink, H W; Sibinga, C T

1998-02-07

An invitational conference was held on September 11, 1996 by the Medical Advisory Commission to the Blood Transfusion Council of the Netherlands Red Cross, addressing the issues of 'maximal' versus 'optimal' safety measures for the blood supply. Invited were blood transfusion specialists, clinicians, representatives of patient interest groups, the Ministry and Inspectorate of Health and members of parliament. Transfusion experts and clinicians were found to advocate an optimal course, following strategies of evidence-based medicine, cost-benefit analyses and medical technology assessment. Patient groups depending on blood products, such as haemophilia patients would rather opt for maximal safety. Insurance companies would choose likewise, to exclude any risk if possible. Health care juridical advisers would advise to choose for optimal safety, but to reserve funds covering the differences with 'maximal safety' in case of litigation. Politicians and the general public would sooner choose for maximal rather than optimal security. The overall impression persists that however small the statistical risk may be, in the eyes of many it is unacceptable. This view is very stubborn.

Risk based approach for design and optimization of stomach specific delivery of rifampicin.

PubMed

Vora, Chintan; Patadia, Riddhish; Mittal, Karan; Mashru, Rajashree

2013-10-15

The research envisaged focuses on risk management approach for better recognizing the risks, ways to mitigate them and propose a control strategy for the development of rifampicin gastroretentive tablets. Risk assessment using failure mode and effects analysis (FMEA) was done to depict the effects of specific failure modes related to respective formulation/process variable. A Box-Behnken design was used to investigate the effect of amount of sodium bicarbonate (X1), pore former HPMC (X2) and glyceryl behenate (X3) on percent drug release at 1st hour (Q1), 4th hour (Q4), 8th hour (Q8) and floating lag time (min). Main effects and interaction plots were generated to study effects of variables. Selection of the optimized formulation was done using desirability function and overlay contour plots. The optimized formulation exhibited Q1 of 20.9%, Q4 of 59.1%, Q8 of 94.8% and floating lag time of 4.0 min. Akaike information criteria and Model selection criteria revealed that the model was best described by Korsmeyer-Peppas power law. The residual plots demonstrated no existence of non-normality, skewness or outliers. The composite desirability for optimized formulation computed using equations and software were 0.84 and 0.86 respectively. FTIR, DSC and PXRD studies ruled out drug polymer interaction due to thermal treatment. Copyright © 2013 Elsevier B.V. All rights reserved.

Risk assessment and experimental design in the development of a prolonged release drug delivery system with paliperidone.

PubMed

Iurian, Sonia; Turdean, Luana; Tomuta, Ioan

2017-01-01

This study focuses on the development of a drug product based on a risk assessment-based approach, within the quality by design paradigm. A prolonged release system was proposed for paliperidone (Pal) delivery, containing Kollidon ® SR as an insoluble matrix agent and hydroxypropyl cellulose, hydroxypropyl methylcellulose (HPMC), or sodium carboxymethyl cellulose as a hydrophilic polymer. The experimental part was preceded by the identification of potential sources of variability through Ishikawa diagrams, and failure mode and effects analysis was used to deliver the critical process parameters that were further optimized by design of experiments. A D-optimal design was used to investigate the effects of Kollidon SR ratio ( X 1 ), the type of hydrophilic polymer ( X 2 ), and the percentage of hydrophilic polymer ( X 3 ) on the percentages of dissolved Pal over 24 h ( Y 1 - Y 9 ). Effects expressed as regression coefficients and response surfaces were generated, along with a design space for the preparation of a target formulation in an experimental area with low error risk. The optimal formulation contained 27.62% Kollidon SR and 8.73% HPMC and achieved the prolonged release of Pal, with low burst effect, at ratios that were very close to the ones predicted by the model. Thus, the parameters with the highest impact on the final product quality were studied, and safe ranges were established for their variations. Finally, a risk mitigation and control strategy was proposed to assure the quality of the system, by constant process monitoring.

Nonstationary decision model for flood risk decision scaling

NASA Astrophysics Data System (ADS)

Spence, Caitlin M.; Brown, Casey M.

2016-11-01

Hydroclimatic stationarity is increasingly questioned as a default assumption in flood risk management (FRM), but successor methods are not yet established. Some potential successors depend on estimates of future flood quantiles, but methods for estimating future design storms are subject to high levels of uncertainty. Here we apply a Nonstationary Decision Model (NDM) to flood risk planning within the decision scaling framework. The NDM combines a nonstationary probability distribution of annual peak flow with optimal selection of flood management alternatives using robustness measures. The NDM incorporates structural and nonstructural FRM interventions and valuation of flows supporting ecosystem services to calculate expected cost of a given FRM strategy. A search for the minimum-cost strategy under incrementally varied representative scenarios extending across the plausible range of flood trend and value of the natural flow regime discovers candidate FRM strategies that are evaluated and compared through a decision scaling analysis (DSA). The DSA selects a management strategy that is optimal or close to optimal across the broadest range of scenarios or across the set of scenarios deemed most likely to occur according to estimates of future flood hazard. We illustrate the decision framework using a stylized example flood management decision based on the Iowa City flood management system, which has experienced recent unprecedented high flow episodes. The DSA indicates a preference for combining infrastructural and nonstructural adaptation measures to manage flood risk and makes clear that options-based approaches cannot be assumed to be "no" or "low regret."

Optimizing timing and dosage: does parent type moderate the effects of variations of a parent-based intervention to reduce college student drinking?

PubMed

Varvil-Weld, Lindsey; Scaglione, Nichole; Cleveland, Michael J; Mallett, Kimberly A; Turrisi, Rob; Abar, Caitlin C

2014-02-01

Research on parent-based interventions (PBIs) to reduce college student drinking has explored the optimal timing of delivery and dosage. The present study extended this work by examining the effectiveness of three different PBI conditions on student drinking outcomes as a function of parenting types and students' pre-college drinking patterns. Four hypotheses were evaluated (early intervention, increased dosage, invariant, and treatment matching risk). A random sample of 1,900 college students and their parents was randomized to four conditions: (1) pre-college matriculation, (2) pre-college matriculation plus booster, (3) post-college matriculation, or (4) control, and was assessed at baseline (summer prior to college) and 5-month follow-up. Baseline parent type was assessed using latent profile analysis (positive, pro-alcohol, positive, anti-alcohol, negative mother, and negative father). Student drinking patterns were classified at baseline and follow-up and included: non-drinker, weekend light drinker, weekend heavy episodic drinker, and heavy drinker. Consistent with the treatment matching risk hypothesis, results indicated parent type moderated the effects of intervention condition such that receiving the intervention prior to college was associated with lower likelihood of being in a higher-risk drinking pattern at follow-up for students with positive, anti-alcohol, or negative father parent types. The findings are discussed with respect to optimal delivery and dosage of parent-based interventions for college student drinking.

Optimizing Timing and Dosage: Does Parent Type Moderate the Effects of Variations of a Parent-Based Intervention to Reduce College Student Drinking?

PubMed Central

Varvil-Weld, Lindsey; Scaglione, Nichole; Cleveland, Michael J.; Mallett, Kimberly A.; Turrisi, Rob; Abar, Caitlin C.

2013-01-01

Research on parent-based interventions (PBIs) to reduce college student drinking has explored the optimal timing of delivery and dosage. The present study extended this work by examining the effectiveness of three different PBI conditions on student drinking outcomes as a function of parenting types and students' pre-college drinking patterns. Four hypotheses were evaluated (early intervention, increased dosage, invariant, and treatment matching risk). A random sample of 1900 college students and their parents was randomized to four conditions: 1) pre-college matriculation, 2) pre-college matriculation plus booster, 3) post-college matriculation, or 4) control, and was assessed at baseline (summer prior to college) and 5-month follow-up. Baseline parent type was assessed using latent profile analysis (positive, pro-alcohol, positive, anti-alcohol, negative mother and negative father). Student drinking patterns were classified at baseline and follow up and included: non-drinker, weekend light drinker, weekend heavy episodic drinker, and heavy drinker. Consistent with the treatment matching risk hypothesis, results indicated parent type moderated the effects of intervention condition such that receiving the intervention prior to college was associated with lower likelihood of being in a higher-risk drinking pattern at follow up for students with positive, anti-alcohol or negative father parent types. The findings are discussed with respect to optimal delivery and dosage of parent-based interventions for college student drinking. PMID:23404668

Testing a hydraulic trait based model of stomatal control: results from a controlled drought experiment on aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas)

NASA Astrophysics Data System (ADS)

Love, D. M.; Venturas, M.; Sperry, J.; Wang, Y.; Anderegg, W.

2017-12-01

Modeling approaches for tree stomatal control often rely on empirical fitting to provide accurate estimates of whole tree transpiration (E) and assimilation (A), which are limited in their predictive power by the data envelope used to calibrate model parameters. Optimization based models hold promise as a means to predict stomatal behavior under novel climate conditions. We designed an experiment to test a hydraulic trait based optimization model, which predicts stomatal conductance from a gain/risk approach. Optimal stomatal conductance is expected to maximize the potential carbon gain by photosynthesis, and minimize the risk to hydraulic transport imposed by cavitation. The modeled risk to the hydraulic network is assessed from cavitation vulnerability curves, a commonly measured physiological trait in woody plant species. Over a growing season garden grown plots of aspen (Populus tremuloides, Michx.) and ponderosa pine (Pinus ponderosa, Douglas) were subjected to three distinct drought treatments (moderate, severe, severe with rehydration) relative to a control plot to test model predictions. Model outputs of predicted E, A, and xylem pressure can be directly compared to both continuous data (whole tree sapflux, soil moisture) and point measurements (leaf level E, A, xylem pressure). The model also predicts levels of whole tree hydraulic impairment expected to increase mortality risk. This threshold is used to estimate survivorship in the drought treatment plots. The model can be run at two scales, either entirely from climate (meteorological inputs, irrigation) or using the physiological measurements as a starting point. These data will be used to study model performance and utility, and aid in developing the model for larger scale applications.

A Robust Statistics Approach to Minimum Variance Portfolio Optimization

NASA Astrophysics Data System (ADS)

Yang, Liusha; Couillet, Romain; McKay, Matthew R.

2015-12-01

We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of available market returns is often of similar order to the number of assets, so that the sample covariance matrix performs poorly as a covariance estimator. Additionally, financial market data often contain outliers which, if not correctly handled, may further corrupt the covariance estimation. We address these shortcomings by studying the performance of a hybrid covariance matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's shrinkage estimator while assuming samples with heavy-tailed distribution. Employing recent results from random matrix theory, we develop a consistent estimator of (a scaled version of) the realized portfolio risk, which is minimized by optimizing online the shrinkage intensity. Our portfolio optimization method is shown via simulations to outperform existing methods both for synthetic and real market data.

Optimizing global liver function in radiation therapy treatment planning

NASA Astrophysics Data System (ADS)

Wu, Victor W.; Epelman, Marina A.; Wang, Hesheng; Romeijn, H. Edwin; Feng, Mary; Cao, Yue; Ten Haken, Randall K.; Matuszak, Martha M.

2016-09-01

Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (\\ell \\text{EUD} ) (conventional ‘\\ell \\text{EUD} model’), the so-called perfusion-weighted \\ell \\text{EUD} (\\text{fEUD} ) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting \\ell \\text{EUD} , fEUD, and GLF plans delivering the same target \\ell \\text{EUD} are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6 % ≤ft(7.5 % \\right) more liver function than the fEUD (\\ell \\text{EUD} ) plan does in 2D cases, and up to 4.5 % ≤ft(5.6 % \\right) in 3D cases. The GLF and fEUD plans worsen in \\ell \\text{EUD} of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and often achieves better GLF than \\ell \\text{EUD} model optimization does, the GLF model directly optimizes a more clinically relevant metric and can further improve fEUD plan quality.

Risk modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

2013-09-01

Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

Communication of uncertainty regarding individualized cancer risk estimates: effects and influential factors.

PubMed

Han, Paul K J; Klein, William M P; Lehman, Tom; Killam, Bill; Massett, Holly; Freedman, Andrew N

2011-01-01

To examine the effects of communicating uncertainty regarding individualized colorectal cancer risk estimates and to identify factors that influence these effects. Two Web-based experiments were conducted, in which adults aged 40 years and older were provided with hypothetical individualized colorectal cancer risk estimates differing in the extent and representation of expressed uncertainty. The uncertainty consisted of imprecision (otherwise known as "ambiguity") of the risk estimates and was communicated using different representations of confidence intervals. Experiment 1 (n = 240) tested the effects of ambiguity (confidence interval v. point estimate) and representational format (textual v. visual) on cancer risk perceptions and worry. Potential effect modifiers, including personality type (optimism), numeracy, and the information's perceived credibility, were examined, along with the influence of communicating uncertainty on responses to comparative risk information. Experiment 2 (n = 135) tested enhanced representations of ambiguity that incorporated supplemental textual and visual depictions. Communicating uncertainty led to heightened cancer-related worry in participants, exemplifying the phenomenon of "ambiguity aversion." This effect was moderated by representational format and dispositional optimism; textual (v. visual) format and low (v. high) optimism were associated with greater ambiguity aversion. However, when enhanced representations were used to communicate uncertainty, textual and visual formats showed similar effects. Both the communication of uncertainty and use of the visual format diminished the influence of comparative risk information on risk perceptions. The communication of uncertainty regarding cancer risk estimates has complex effects, which include heightening cancer-related worry-consistent with ambiguity aversion-and diminishing the influence of comparative risk information on risk perceptions. These responses are influenced by representational format and personality type, and the influence of format appears to be modifiable and content dependent.

Poster — Thur Eve — 61: A new framework for MPERT plan optimization using MC-DAO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, M; Lloyd, S AM; Townson, R

2014-08-15

This work combines the inverse planning technique known as Direct Aperture Optimization (DAO) with Intensity Modulated Radiation Therapy (IMRT) and combined electron and photon therapy plans. In particular, determining conditions under which Modulated Photon/Electron Radiation Therapy (MPERT) produces better dose conformality and sparing of organs at risk than traditional IMRT plans is central to the project. Presented here are the materials and methods used to generate and manipulate the DAO procedure. Included is the introduction of a powerful Java-based toolkit, the Aperture-based Monte Carlo (MC) MPERT Optimizer (AMMO), that serves as a framework for optimization and provides streamlined access tomore » underlying particle transport packages. Comparison of the toolkit's dose calculations to those produced by the Eclipse TPS and the demonstration of a preliminary optimization are presented as first benchmarks. Excellent agreement is illustrated between the Eclipse TPS and AMMO for a 6MV photon field. The results of a simple optimization shows the functioning of the optimization framework, while significant research remains to characterize appropriate constraints.« less

Breast cancer screening in an era of personalized regimens: a conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level.

PubMed

Onega, Tracy; Beaber, Elisabeth F; Sprague, Brian L; Barlow, William E; Haas, Jennifer S; Tosteson, Anna N A; D Schnall, Mitchell; Armstrong, Katrina; Schapira, Marilyn M; Geller, Berta; Weaver, Donald L; Conant, Emily F

2014-10-01

Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women's health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for "overdiagnosis," and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a "1-size-fits-all" guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women's risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform. © 2014 American Cancer Society.

A Machine-Learning and Filtering Based Data Assimilation Framework for Geologic Carbon Sequestration Monitoring Optimization

NASA Astrophysics Data System (ADS)

Chen, B.; Harp, D. R.; Lin, Y.; Keating, E. H.; Pawar, R.

2017-12-01

Monitoring is a crucial aspect of geologic carbon sequestration (GCS) risk management. It has gained importance as a means to ensure CO2 is safely and permanently stored underground throughout the lifecycle of a GCS project. Three issues are often involved in a monitoring project: (i) where is the optimal location to place the monitoring well(s), (ii) what type of data (pressure, rate and/or CO2 concentration) should be measured, and (iii) What is the optimal frequency to collect the data. In order to address these important issues, a filtering-based data assimilation procedure is developed to perform the monitoring optimization. The optimal monitoring strategy is selected based on the uncertainty reduction of the objective of interest (e.g., cumulative CO2 leak) for all potential monitoring strategies. To reduce the computational cost of the filtering-based data assimilation process, two machine-learning algorithms: Support Vector Regression (SVR) and Multivariate Adaptive Regression Splines (MARS) are used to develop the computationally efficient reduced-order-models (ROMs) from full numerical simulations of CO2 and brine flow. The proposed framework for GCS monitoring optimization is demonstrated with two examples: a simple 3D synthetic case and a real field case named Rock Spring Uplift carbon storage site in Southwestern Wyoming.

Reliability Based Design for a Raked Wing Tip of an Airframe

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2011-01-01

A reliability-based optimization methodology has been developed to design the raked wing tip of the Boeing 767-400 extended range airliner made of composite and metallic materials. Design is formulated for an accepted level of risk or reliability. The design variables, weight and the constraints became functions of reliability. Uncertainties in the load, strength and the material properties, as well as the design variables, were modeled as random parameters with specified distributions, like normal, Weibull or Gumbel functions. The objective function and constraint, or a failure mode, became derived functions of the risk-level. Solution to the problem produced the optimum design with weight, variables and constraints as a function of the risk-level. Optimum weight versus reliability traced out an inverted-S shaped graph. The center of the graph corresponded to a 50 percent probability of success, or one failure in two samples. Under some assumptions, this design would be quite close to the deterministic optimum solution. The weight increased when reliability exceeded 50 percent, and decreased when the reliability was compromised. A design could be selected depending on the level of risk acceptable to a situation. The optimization process achieved up to a 20-percent reduction in weight over traditional design.

Body mass index, waist circumference and waist-to-hip ratio cut-off points for categorisation of obesity among Omani Arabs.

PubMed

Al-Lawati, Jawad A; Jousilahti, Pekka

2008-01-01

There are no data on optimal cut-off points to classify obesity among Omani Arabs. The existing cut-off points were obtained from studies of European populations. To determine gender-specific optimal cut-off points for body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) associated with elevated prevalent cardiovascular disease (CVD) risk among Omani Arabs. A community-based cross-sectional study. The survey was conducted in the city of Nizwa in Oman in 2001. The study contained a probabilistic random sample of 1421 adults aged > or =20 years. Prevalent CVD risk was defined as the presence of at least two of the following three risk factors: hyperglycaemia, hypertension and dyslipidaemia. Logistic regression and receiver-operating characteristic (ROC) curve analyses were used to determine optimal cut-off points for BMI, WC and WHR in relation to the area under the curve (AUC), sensitivity and specificity. Over 87% of Omanis had at least one CVD risk factor (38% had hyperglycaemia, 19% hypertension and 34.5% had high total cholesterol). All three indices including BMI (AUC = 0.766), WC (AUC = 0.772) and WHR (AUC = 0.767) predicted prevalent CVD risk factors equally well. The optimal cut-off points for men and women respectively were 23.2 and 26.8 kg m-2 for BMI, 80.0 and 84.5 cm for WC, and 0.91 and 0.91 for WHR. To identify Omani subjects of Arab ethnicity at high risk of CVD, cut-off points lower than currently recommended for BMI, WC and WHR are needed for men while higher cut-off points are suggested for women.

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers.

PubMed

Maniruzzaman, Md; Rahman, Md Jahanur; Al-MehediHasan, Md; Suri, Harman S; Abedin, Md Menhazul; El-Baz, Ayman; Suri, Jasjit S

2018-04-10

Diabetes mellitus is a group of metabolic diseases in which blood sugar levels are too high. About 8.8% of the world was diabetic in 2017. It is projected that this will reach nearly 10% by 2045. The major challenge is that when machine learning-based classifiers are applied to such data sets for risk stratification, leads to lower performance. Thus, our objective is to develop an optimized and robust machine learning (ML) system under the assumption that missing values or outliers if replaced by a median configuration will yield higher risk stratification accuracy. This ML-based risk stratification is designed, optimized and evaluated, where: (i) the features are extracted and optimized from the six feature selection techniques (random forest, logistic regression, mutual information, principal component analysis, analysis of variance, and Fisher discriminant ratio) and combined with ten different types of classifiers (linear discriminant analysis, quadratic discriminant analysis, naïve Bayes, Gaussian process classification, support vector machine, artificial neural network, Adaboost, logistic regression, decision tree, and random forest) under the hypothesis that both missing values and outliers when replaced by computed medians will improve the risk stratification accuracy. Pima Indian diabetic dataset (768 patients: 268 diabetic and 500 controls) was used. Our results demonstrate that on replacing the missing values and outliers by group median and median values, respectively and further using the combination of random forest feature selection and random forest classification technique yields an accuracy, sensitivity, specificity, positive predictive value, negative predictive value and area under the curve as: 92.26%, 95.96%, 79.72%, 91.14%, 91.20%, and 0.93, respectively. This is an improvement of 10% over previously developed techniques published in literature. The system was validated for its stability and reliability. RF-based model showed the best performance when outliers are replaced by median values.

Limitations in predicting PAM50 intrinsic subtype and risk of relapse score with Ki67 in estrogen receptor-positive HER2-negative breast cancer

PubMed Central

Fernand ez-Martinez, Aranzazu; Pascual, Tomás; Perrone, Giuseppe; Morales, Serafin; de la Haba, Juan; González-Rivera, Milagros; Galván, Patricia; Zalfa, Francesca; Amato, Michela; Gonzalez, Lucia; Prats, Miquel; Rojo, Federico; Manso, Luis; Paré, Laia; Alonso, Immaculada; Albanell, Joan; Vivancos, Ana; González, Antonio; Matito, Judit; González, Sonia; Fernandez, Pedro; Adamo, Barbara; Muñoz, Montserrat; Viladot, Margarita; Font, Carme; Aya, Francisco; Vidal, Maria; Caballero, Rosalía; Carrasco, Eva; Altomare, Vittorio; Tonini, Giuseppe; Prat, Aleix; Martin, Miguel

2017-01-01

PAM50/Prosigna gene expression-based assay identifies three categorical risk of relapse groups (ROR-low, ROR-intermediate and ROR-high) in post-menopausal patients with estrogen receptor estrogen receptor-positive (ER+)/ HER2-negative (HER2-) early breast cancer. Low risk patients might not need adjuvant chemotherapy since their risk of distant relapse at 10-years is below 10% with endocrine therapy only. In this study, 517 consecutive patients with ER+/HER2- and node-negative disease were evaluated for Ki67 and Prosigna. Most of Luminal A tumors (65.6%) and ROR-low tumors (70.9%) had low Ki67 values (0-10%); however, the percentage of patients with ROR-medium or ROR-high disease within the Ki67 0-10% group was 42.7% (with tumor sizes ≤2 cm) and 33.9% (with tumor sizes > 2 cm). Finally, we found that the optimal Ki67 cutoff for identifying Luminal A or ROR-low tumors was 14%. Ki67 as a surrogate biomarker in identifying Prosigna low-risk outcome patients or Luminal A disease in the clinical setting is unreliable. In the absence of a well-validated prognostic gene expression-based assay, the optimal Ki67 cutoff for identifying low-risk outcome patients or Luminal A disease remains at 14%. PMID:28423537

Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view.

PubMed

Li, Xiaohong; Blount, Patricia L; Vaughan, Thomas L; Reid, Brian J

2011-02-01

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.

Cancer risk communication in mainstream and ethnic newspapers.

PubMed

Stryker, Jo Ellen; Fishman, Jessica; Emmons, Karen M; Viswanath, Kasisomayajula

2009-01-01

We wanted to understand how cancer risks are communicated in mainstream and ethnic newspapers, to determine whether the 2 kinds of newspapers differ and to examine features of news stories and sources that might predict optimal risk communication. Optimal risk communication was defined as presenting the combination of absolute risk, relative risk, and prevention response efficacy information. We collected data by conducting a content analysis of cancer news coverage from 2003 (5,327 stories in major newspapers, 565 stories in ethnic newspapers). Comparisons of mainstream and ethnic newspapers were conducted by using cross-tabulations and Pearson chi2 tests for significance. Logistic regression equations were computed to calculate odds ratios and 95% confidence intervals for optimal risk communication. In both kinds of newspapers, cancer risks were rarely communicated numerically. When numeric presentations of cancer risks were used, only 26.2% of mainstream and 29.5% of ethnic newspaper stories provided estimates of both absolute and relative risk. For both kinds of papers, only 19% of news stories presented risk communication optimally. Cancer risks were more likely to be communicated optimally if they focused on prostate cancer, were reports of new research, or discussed medical or demographic risks. Research is needed to understand how these nonnumeric and decontextualized presentations of risk might contribute to inaccurate risk perceptions among news consumers.

The Optimal Timing of Stage-2-Palliation After the Norwood Operation.

PubMed

Meza, James M; Hickey, Edward; McCrindle, Brian; Blackstone, Eugene; Anderson, Brett; Overman, David; Kirklin, James K; Karamlou, Tara; Caldarone, Christopher; Kim, Richard; DeCampli, William; Jacobs, Marshall; Guleserian, Kristine; Jacobs, Jeffrey P; Jaquiss, Robert

2018-01-01

The effect of the timing of stage-2-palliation (S2P) on survival through single ventricle palliation remains unknown. This study investigated the optimal timing of S2P that minimizes pre-S2P attrition and maximizes post-S2P survival. The Congenital Heart Surgeons' Society's critical left ventricular outflow tract obstruction cohort was used. Survival analysis was performed using multiphase parametric hazard analysis. Separate risk factors for death after the Norwood and after S2P were identified. Based on the multivariable models, infants were stratified as low, intermediate, or high risk. Cumulative 2-year, post-Norwood survival was predicted. Optimal timing was determined using conditional survival analysis and plotted as 2-year, post-Norwood survival versus age at S2P. A Norwood operation was performed in 534 neonates from 21 institutions. The S2P was performed in 71%, at a median age of 5.1 months (IQR: 4.3 to 6.0), and 22% died after Norwood. By 5 years after S2P, 10% of infants had died. For low- and intermediate-risk infants, performing S2P after age 3 months was associated with 89% ± 3% and 82% ± 3% 2-year survival, respectively. Undergoing an interval cardiac reoperation or moderate-severe right ventricular dysfunction before S2P were high-risk features. Among high-risk infants, 2-year survival was 63% ± 5%, and even lower when S2P was performed before age 6 months. Performing S2P after age 3 months may optimize survival of low- and intermediate-risk infants. High-risk infants are unlikely to complete three-stage palliation, and early S2P may increase their risk of mortality. We infer that early referral for cardiac transplantation may increase their chance of survival. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

NASA Astrophysics Data System (ADS)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

An individual risk prediction model for lung cancer based on a study in a Chinese population.

PubMed

Wang, Xu; Ma, Kewei; Cui, Jiuwei; Chen, Xiao; Jin, Lina; Li, Wei

2015-01-01

Early detection and diagnosis remains an effective yet challenging approach to improve the clinical outcome of patients with cancer. Low-dose computed tomography screening has been suggested to improve the diagnosis of lung cancer in high-risk individuals. To make screening more efficient, it is necessary to identify individuals who are at high risk. We conducted a case-control study to develop a predictive model for identification of such high-risk individuals. Clinical data from 705 lung cancer patients and 988 population-based controls were used for the development and evaluation of the model. Associations between environmental variants and lung cancer risk were analyzed with a logistic regression model. The predictive accuracy of the model was determined by calculating the area under the receiver operating characteristic curve and the optimal operating point. Our results indicate that lung cancer risk factors included older age, male gender, lower education level, family history of cancer, history of chronic obstructive pulmonary disease, lower body mass index, smoking cigarettes, a diet with less seafood, vegetables, fruits, dairy products, soybean products and nuts, a diet rich in meat, and exposure to pesticides and cooking emissions. The area under the curve was 0.8851 and the optimal operating point was obtained. With a cutoff of 0.35, the false positive rate, true positive rate, and Youden index were 0.21, 0.87, and 0.66, respectively. The risk prediction model for lung cancer developed in this study could discriminate high-risk from low-risk individuals.

Acute Intraoperative Pulmonary Aspiration

PubMed Central

Nason, Katie S.

2015-01-01

Synopsis Acute intraoperative aspiration is a potentially fatal complication with significant associated morbidity. Patients undergoing thoracic surgery are at increased risk for anesthesia-related aspiration, largely due to the predisposing conditions associated with this complication. Awareness of the risk factors, predisposing conditions, maneuvers to decrease risk and immediate management options by both the thoracic surgeon and the anesthesia team is imperative to reducing risk and optimizing patient outcomes associated with acute intraoperative pulmonary aspiration. Based on the root-cause analyses that many of the aspiration events can be traced back to provider factors, having an experienced anesthesiologist present for high-risk cases is also critical. PMID:26210926

Credibilistic multi-period portfolio optimization based on scenario tree

NASA Astrophysics Data System (ADS)

Mohebbi, Negin; Najafi, Amir Abbas

2018-02-01

In this paper, we consider a multi-period fuzzy portfolio optimization model with considering transaction costs and the possibility of risk-free investment. We formulate a bi-objective mean-VaR portfolio selection model based on the integration of fuzzy credibility theory and scenario tree in order to dealing with the markets uncertainty. The scenario tree is also a proper method for modeling multi-period portfolio problems since the length and continuity of their horizon. We take the return and risk as well cardinality, threshold, class, and liquidity constraints into consideration for further compliance of the model with reality. Then, an interactive dynamic programming method, which is based on a two-phase fuzzy interactive approach, is employed to solve the proposed model. In order to verify the proposed model, we present an empirical application in NYSE under different circumstances. The results show that the consideration of data uncertainty and other real-world assumptions lead to more practical and efficient solutions.

Comparative evaluation of two dose optimization methods for image-guided, highly-conformal, tandem and ovoids cervix brachytherapy planning

NASA Astrophysics Data System (ADS)

Ren, Jiyun; Menon, Geetha; Sloboda, Ron

2013-04-01

Although the Manchester system is still extensively used to prescribe dose in brachytherapy (BT) for locally advanced cervix cancer, many radiation oncology centers are transitioning to 3D image-guided BT, owing to the excellent anatomy definition offered by modern imaging modalities. As automatic dose optimization is highly desirable for 3D image-based BT, this study comparatively evaluates the performance of two optimization methods used in BT treatment planning—Nelder-Mead simplex (NMS) and simulated annealing (SA)—for a cervix BT computer simulation model incorporating a Manchester-style applicator. Eight model cases were constructed based on anatomical structure data (for high risk-clinical target volume (HR-CTV), bladder, rectum and sigmoid) obtained from measurements on fused MR-CT images for BT patients. D90 and V100 for HR-CTV, D2cc for organs at risk (OARs), dose to point A, conformation index and the sum of dwell times within the tandem and ovoids were calculated for optimized treatment plans designed to treat the HR-CTV in a highly conformal manner. Compared to the NMS algorithm, SA was found to be superior as it could perform optimization starting from a range of initial dwell times, while the performance of NMS was strongly dependent on their initial choice. SA-optimized plans also exhibited lower D2cc to OARs, especially the bladder and sigmoid, and reduced tandem dwell times. For cases with smaller HR-CTV having good separation from adjoining OARs, multiple SA-optimized solutions were found which differed markedly from each other and were associated with different choices for initial dwell times. Finally and importantly, the SA method yielded plans with lower dwell time variability compared with the NMS method.

Risk-based decision making to manage water quality failures caused by combined sewer overflows

NASA Astrophysics Data System (ADS)

Sriwastava, A. K.; Torres-Matallana, J. A.; Tait, S.; Schellart, A.

2017-12-01

Regulatory authorities set certain environmental permit for water utilities such that the combined sewer overflows (CSO) managed by these companies conform to the regulations. These utility companies face the risk of paying penalty or negative publicity in case they breach the environmental permit. These risks can be addressed by designing appropriate solutions such as investing in additional infrastructure which improve the system capacity and reduce the impact of CSO spills. The performance of these solutions is often estimated using urban drainage models. Hence, any uncertainty in these models can have a significant effect on the decision making process. This study outlines a risk-based decision making approach to address water quality failure caused by CSO spills. A calibrated lumped urban drainage model is used to simulate CSO spill quality in Haute-Sûre catchment in Luxembourg. Uncertainty in rainfall and model parameters is propagated through Monte Carlo simulations to quantify uncertainty in the concentration of ammonia in the CSO spill. A combination of decision alternatives such as the construction of a storage tank at the CSO and the reduction in the flow contribution of catchment surfaces are selected as planning measures to avoid the water quality failure. Failure is defined as exceedance of a concentration-duration based threshold based on Austrian emission standards for ammonia (De Toffol, 2006) with a certain frequency. For each decision alternative, uncertainty quantification results into a probability distribution of the number of annual CSO spill events which exceed the threshold. For each alternative, a buffered failure probability as defined in Rockafellar & Royset (2010), is estimated. Buffered failure probability (pbf) is a conservative estimate of failure probability (pf), however, unlike failure probability, it includes information about the upper tail of the distribution. A pareto-optimal set of solutions is obtained by performing mean- pbf optimization. The effectiveness of using buffered failure probability compared to the failure probability is tested by comparing the solutions obtained by using mean-pbf and mean-pf optimizations.

Optimal Duration of Antibiotic Therapy in Patients With Hematogenous Vertebral Osteomyelitis at Low Risk and High Risk of Recurrence.

PubMed

Park, Ki-Ho; Cho, Oh-Hyun; Lee, Jung Hee; Park, Ji Seon; Ryu, Kyung Nam; Park, Seong Yeon; Lee, Yu-Mi; Chong, Yong Pil; Kim, Sung-Han; Lee, Sang-Oh; Choi, Sang-Ho; Bae, In-Gyu; Kim, Yang Soo; Woo, Jun Hee; Lee, Mi Suk

2016-05-15

The optimal duration of antibiotic treatment for hematogenous vertebral osteomyelitis (HVO) should be based on the patient's risk of recurrence, but it is not well established. A retrospective review was conducted to evaluate the optimal duration of antibiotic treatment in patients with HVO at low and high risk of recurrence. Patients with at least 1 independent baseline risk factor for recurrence, determined by multivariable analysis, were considered as high risk and those with no risk factor as low risk. A total of 314 patients with microbiologically diagnosed HVO were evaluable for recurrence. In multivariable analysis, methicillin-resistant Staphylococcus aureus infection (adjusted odds ratio [aOR], 2.61; 95% confidence interval [CI], 1.16-5.87), undrained paravertebral/psoas abscesses (aOR, 4.09; 95% CI, 1.82-9.19), and end-stage renal disease (aOR, 6.58; 95% CI, 1.63-26.54) were independent baseline risk factors for recurrence. Therefore, 191 (60.8%) patients were classified as low risk and 123 (39.2%) as high risk. Among high-risk patients, there was a significant decreasing trend for recurrence according to total duration of antibiotic therapy: 34.8% (4-6 weeks [28-41 days]), 29.6% (6-8 weeks [42-55 days]), and 9.6% (≥8 weeks [≥56 days]) (P = .002). For low-risk patients, this association was still significant but the recurrence rates were much lower: 12.0% (4-6 weeks), 6.3% (6-8 weeks), and 2.2% (≥8 weeks) (P = .02). Antibiotic therapy of prolonged duration (≥8 weeks) should be given to patients with HVO at high risk of recurrence. For low-risk patients, a shorter duration (6-8 weeks) of pathogen-directed antibiotic therapy may be sufficient. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes.

PubMed

Wang, Yuanjia; Chen, Tianle; Zeng, Donglin

2016-01-01

Learning risk scores to predict dichotomous or continuous outcomes using machine learning approaches has been studied extensively. However, how to learn risk scores for time-to-event outcomes subject to right censoring has received little attention until recently. Existing approaches rely on inverse probability weighting or rank-based regression, which may be inefficient. In this paper, we develop a new support vector hazards machine (SVHM) approach to predict censored outcomes. Our method is based on predicting the counting process associated with the time-to-event outcomes among subjects at risk via a series of support vector machines. Introducing counting processes to represent time-to-event data leads to a connection between support vector machines in supervised learning and hazards regression in standard survival analysis. To account for different at risk populations at observed event times, a time-varying offset is used in estimating risk scores. The resulting optimization is a convex quadratic programming problem that can easily incorporate non-linearity using kernel trick. We demonstrate an interesting link from the profiled empirical risk function of SVHM to the Cox partial likelihood. We then formally show that SVHM is optimal in discriminating covariate-specific hazard function from population average hazard function, and establish the consistency and learning rate of the predicted risk using the estimated risk scores. Simulation studies show improved prediction accuracy of the event times using SVHM compared to existing machine learning methods and standard conventional approaches. Finally, we analyze two real world biomedical study data where we use clinical markers and neuroimaging biomarkers to predict age-at-onset of a disease, and demonstrate superiority of SVHM in distinguishing high risk versus low risk subjects.

Alternative evaluation metrics for risk adjustment methods.

PubMed

Park, Sungchul; Basu, Anirban

2018-06-01

Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk-adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high-expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk-adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013-2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution-based estimators achieve higher group-level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual-level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade-off in selecting an appropriate risk-adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors. Copyright © 2018 John Wiley & Sons, Ltd.

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

NASA Technical Reports Server (NTRS)

Kerstman, Eric L.; Minard, Charles; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

NASA Astrophysics Data System (ADS)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

2014-06-01

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator

NASA Astrophysics Data System (ADS)

Bol, G. H.; Hissoiny, S.; Lagendijk, J. J. W.; Raaymakers, B. W.

2012-03-01

The MRI accelerator, a combination of a 6 MV linear accelerator with a 1.5 T MRI, facilitates continuous patient anatomy updates regarding translations, rotations and deformations of targets and organs at risk. Accounting for these demands high speed, online intensity-modulated radiotherapy (IMRT) re-optimization. In this paper, a fast IMRT optimization system is described which combines a GPU-based Monte Carlo dose calculation engine for online beamlet generation and a fast inverse dose optimization algorithm. Tightly conformal IMRT plans are generated for four phantom cases and two clinical cases (cervix and kidney) in the presence of the magnetic fields of 0 and 1.5 T. We show that for the presented cases the beamlet generation and optimization routines are fast enough for online IMRT planning. Furthermore, there is no influence of the magnetic field on plan quality and complexity, and equal optimization constraints at 0 and 1.5 T lead to almost identical dose distributions.

Optimal approximations for risk measures of sums of lognormals based on conditional expectations

NASA Astrophysics Data System (ADS)

Vanduffel, S.; Chen, X.; Dhaene, J.; Goovaerts, M.; Henrard, L.; Kaas, R.

2008-11-01

In this paper we investigate the approximations for the distribution function of a sum S of lognormal random variables. These approximations are obtained by considering the conditional expectation E[S|[Lambda

Young drivers' optimism bias for accident risk and driving skill: Accountability and insight experience manipulations.

PubMed

White, Melanie J; Cunningham, Lauren C; Titchener, Kirsteen

2011-07-01

This study aimed to determine whether two brief, low cost interventions would reduce young drivers' optimism bias for their driving skills and accident risk perceptions. This tendency for such drivers to perceive themselves as more skillful and less prone to driving accidents than their peers may lead to less engagement in precautionary driving behaviours and a greater engagement in more dangerous driving behaviour. 243 young drivers (aged 17-25 years) were randomly allocated to one of three groups: accountability, insight or control. All participants provided both overall and specific situation ratings of their driving skills and accident risk relative to a typical young driver. Prior to completing the questionnaire, those in the accountability condition were first advised that their driving skills and accident risk would be later assessed via a driving simulator. Those in the insight condition first underwent a difficult computer-based hazard perception task designed to provide participants with insight into their potential limitations when responding to hazards in difficult and unpredictable driving situations. Participants in the control condition completed only the questionnaire. Results showed that the accountability manipulation was effective in reducing optimism bias in terms of participants' comparative ratings of their accident risk in specific situations, though only for less experienced drivers. In contrast, among more experienced males, participants in the insight condition showed greater optimism bias for overall accident risk than their counterparts in the accountability or control groups. There were no effects of the manipulations on drivers' skills ratings. The differential effects of the two types of manipulations on optimism bias relating to one's accident risk in different subgroups of the young driver sample highlight the importance of targeting interventions for different levels of experience. Accountability interventions may be beneficial for less experienced young drivers but the results suggest exercising caution with the use of insight type interventions, particularly hazard perception style tasks, for more experienced young drivers typically still in the provisional stage of graduated licensing systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

Decision-making when data and inferences are not conclusive: risk-benefit and acceptable regret approach.

PubMed

Hozo, Iztok; Schell, Michael J; Djulbegovic, Benjamin

2008-07-01

The absolute truth in research is unobtainable, as no evidence or research hypothesis is ever 100% conclusive. Therefore, all data and inferences can in principle be considered as "inconclusive." Scientific inference and decision-making need to take into account errors, which are unavoidable in the research enterprise. The errors can occur at the level of conclusions that aim to discern the truthfulness of research hypothesis based on the accuracy of research evidence and hypothesis, and decisions, the goal of which is to enable optimal decision-making under present and specific circumstances. To optimize the chance of both correct conclusions and correct decisions, the synthesis of all major statistical approaches to clinical research is needed. The integration of these approaches (frequentist, Bayesian, and decision-analytic) can be accomplished through formal risk:benefit (R:B) analysis. This chapter illustrates the rational choice of a research hypothesis using R:B analysis based on decision-theoretic expected utility theory framework and the concept of "acceptable regret" to calculate the threshold probability of the "truth" above which the benefit of accepting a research hypothesis outweighs its risks.

Measures of Residual Risk with Connections to Regression, Risk Tracking, Surrogate Models, and Ambiguity

DTIC Science & Technology

2015-05-20

original variable. Residual risk can be exempli ed as a quanti cation of the improved situation faced by a hedging investor compared to that of a...distributional information about Yx for every x as well as the computational cost of evaluating R(Yx) for numerous x, for example within an optimization...Still, when g is costly to evaluate , it might be desirable to develop an approximation of R(Yx), x ∈ IRn through regression based on observations {xj

A risk-based coverage model for video surveillance camera control optimization

NASA Astrophysics Data System (ADS)

Zhang, Hongzhou; Du, Zhiguo; Zhao, Xingtao; Li, Peiyue; Li, Dehua

2015-12-01

Visual surveillance system for law enforcement or police case investigation is different from traditional application, for it is designed to monitor pedestrians, vehicles or potential accidents. Visual surveillance risk is defined as uncertainty of visual information of targets and events monitored in present work and risk entropy is introduced to modeling the requirement of police surveillance task on quality and quantity of vide information. the prosed coverage model is applied to calculate the preset FoV position of PTZ camera.

Risk Management Approach & Progress in Cd and Cr6+ Elimination

DTIC Science & Technology

2014-11-18

Documentation Available by 2015? Gaps Conversion Coating- Aluminum Avionics/Electrical- Class 3 9 7 Medium yes- joint service/OEM/ NASA effort to...Optimized conditions validated by NASA . – FRC validation: immersion process – Based on data from the lab Surtec 650V optimization, an 1800-gallon tank...acting similarly, 650V not • Plans: scale up to 80 gallon process line; assess Metalast TCP/HF- EPA and Henkel products; further study 650V

Cascade reservoir flood control operation based on risk grading and warning in the Upper Yellow River

NASA Astrophysics Data System (ADS)

Xuejiao, M.; Chang, J.; Wang, Y.

2017-12-01

Flood risk reduction with non-engineering measures has become the main idea for flood management. It is more effective for flood risk management to take various non-engineering measures. In this paper, a flood control operation model for cascade reservoirs in the Upper Yellow River was proposed to lower the flood risk of the water system with multi-reservoir by combining the reservoir flood control operation (RFCO) and flood early warning together. Specifically, a discharge control chart was employed to build the joint RFCO simulation model for cascade reservoirs in the Upper Yellow River. And entropy-weighted fuzzy comprehensive evaluation method was adopted to establish a multi-factorial risk assessment model for flood warning grade. Furthermore, after determining the implementing mode of countermeasures with future inflow, an intelligent optimization algorithm was used to solve the optimization model for applicable water release scheme. In addition, another model without any countermeasure was set to be a comparative experiment. The results show that the model developed in this paper can further decrease the flood risk of water system with cascade reservoirs. It provides a new approach to flood risk management by coupling flood control operation and flood early warning of cascade reservoirs.

SU-E-T-436: Fluence-Based Trajectory Optimization for Non-Coplanar VMAT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smyth, G; Bamber, JC; Bedford, JL

2015-06-15

Purpose: To investigate a fluence-based trajectory optimization technique for non-coplanar VMAT for brain cancer. Methods: Single-arc non-coplanar VMAT trajectories were determined using a heuristic technique for five patients. Organ at risk (OAR) volume intersected during raytracing was minimized for two cases: absolute volume and the sum of relative volumes weighted by OAR importance. These trajectories and coplanar VMAT formed starting points for the fluence-based optimization method. Iterative least squares optimization was performed on control points 24° apart in gantry rotation. Optimization minimized the root-mean-square (RMS) deviation of PTV dose from the prescription (relative importance 100), maximum dose to the brainstemmore » (10), optic chiasm (5), globes (5) and optic nerves (5), plus mean dose to the lenses (5), hippocampi (3), temporal lobes (2), cochleae (1) and brain excluding other regions of interest (1). Control point couch rotations were varied in steps of up to 10° and accepted if the cost function improved. Final treatment plans were optimized with the same objectives in an in-house planning system and evaluated using a composite metric - the sum of optimization metrics weighted by importance. Results: The composite metric decreased with fluence-based optimization in 14 of the 15 plans. In the remaining case its overall value, and the PTV and OAR components, were unchanged but the balance of OAR sparing differed. PTV RMS deviation was improved in 13 cases and unchanged in two. The OAR component was reduced in 13 plans. In one case the OAR component increased but the composite metric decreased - a 4 Gy increase in OAR metrics was balanced by a reduction in PTV RMS deviation from 2.8% to 2.6%. Conclusion: Fluence-based trajectory optimization improved plan quality as defined by the composite metric. While dose differences were case specific, fluence-based optimization improved both PTV and OAR dosimetry in 80% of cases.« less

Risk assessment and experimental design in the development of a prolonged release drug delivery system with paliperidone

PubMed Central

Iurian, Sonia; Turdean, Luana; Tomuta, Ioan

2017-01-01

This study focuses on the development of a drug product based on a risk assessment-based approach, within the quality by design paradigm. A prolonged release system was proposed for paliperidone (Pal) delivery, containing Kollidon® SR as an insoluble matrix agent and hydroxypropyl cellulose, hydroxypropyl methylcellulose (HPMC), or sodium carboxymethyl cellulose as a hydrophilic polymer. The experimental part was preceded by the identification of potential sources of variability through Ishikawa diagrams, and failure mode and effects analysis was used to deliver the critical process parameters that were further optimized by design of experiments. A D-optimal design was used to investigate the effects of Kollidon SR ratio (X1), the type of hydrophilic polymer (X2), and the percentage of hydrophilic polymer (X3) on the percentages of dissolved Pal over 24 h (Y1–Y9). Effects expressed as regression coefficients and response surfaces were generated, along with a design space for the preparation of a target formulation in an experimental area with low error risk. The optimal formulation contained 27.62% Kollidon SR and 8.73% HPMC and achieved the prolonged release of Pal, with low burst effect, at ratios that were very close to the ones predicted by the model. Thus, the parameters with the highest impact on the final product quality were studied, and safe ranges were established for their variations. Finally, a risk mitigation and control strategy was proposed to assure the quality of the system, by constant process monitoring. PMID:28331293

QbD for pediatric oral lyophilisates development: risk assessment followed by screening and optimization.

PubMed

Casian, Tibor; Iurian, Sonia; Bogdan, Catalina; Rus, Lucia; Moldovan, Mirela; Tomuta, Ioan

2017-12-01

This study proposed the development of oral lyophilisates with respect to pediatric medicine development guidelines, by applying risk management strategies and DoE as an integrated QbD approach. Product critical quality attributes were overviewed by generating Ishikawa diagrams for risk assessment purposes, considering process, formulation and methodology related parameters. Failure Mode Effect Analysis was applied to highlight critical formulation and process parameters with an increased probability of occurrence and with a high impact on the product performance. To investigate the effect of qualitative and quantitative formulation variables D-optimal designs were used for screening and optimization purposes. Process parameters related to suspension preparation and lyophilization were classified as significant factors, and were controlled by implementing risk mitigation strategies. Both quantitative and qualitative formulation variables introduced in the experimental design influenced the product's disintegration time, mechanical resistance and dissolution properties selected as CQAs. The optimum formulation selected through Design Space presented ultra-fast disintegration time (5 seconds), a good dissolution rate (above 90%) combined with a high mechanical resistance (above 600 g load). Combining FMEA and DoE allowed the science based development of a product with respect to the defined quality target profile by providing better insights on the relevant parameters throughout development process. The utility of risk management tools in pharmaceutical development was demonstrated.

Mindfulness-based prevention for eating disorders: A school-based cluster randomized controlled study.

PubMed

Atkinson, Melissa J; Wade, Tracey D

2015-11-01

Successful prevention of eating disorders represents an important goal due to damaging long-term impacts on health and well-being, modest treatment outcomes, and low treatment seeking among individuals at risk. Mindfulness-based approaches have received early support in the treatment of eating disorders, but have not been evaluated as a prevention strategy. This study aimed to assess the feasibility, acceptability, and efficacy of a novel mindfulness-based intervention for reducing the risk of eating disorders among adolescent females, under both optimal (trained facilitator) and task-shifted (non-expert facilitator) conditions. A school-based cluster randomized controlled trial was conducted in which 19 classes of adolescent girls (N = 347) were allocated to a three-session mindfulness-based intervention, dissonance-based intervention, or classes as usual control. A subset of classes (N = 156) receiving expert facilitation were analyzed separately as a proxy for delivery under optimal conditions. Task-shifted facilitation showed no significant intervention effects across outcomes. Under optimal facilitation, students receiving mindfulness demonstrated significant reductions in weight and shape concern, dietary restraint, thin-ideal internalization, eating disorder symptoms, and psychosocial impairment relative to control by 6-month follow-up. Students receiving dissonance showed significant reductions in socio-cultural pressures. There were no statistically significant differences between the two interventions. Moderate intervention acceptability was reported by both students and teaching staff. Findings show promise for the application of mindfulness in the prevention of eating disorders; however, further work is required to increase both impact and acceptability, and to enable successful outcomes when delivered by less expert providers. © 2015 Wiley Periodicals, Inc.

Dynamic optimization of ISR sensors using a risk-based reward function applied to ground and space surveillance scenarios

NASA Astrophysics Data System (ADS)

DeSena, J. T.; Martin, S. R.; Clarke, J. C.; Dutrow, D. A.; Newman, A. J.

2012-06-01

As the number and diversity of sensing assets available for intelligence, surveillance and reconnaissance (ISR) operations continues to expand, the limited ability of human operators to effectively manage, control and exploit the ISR ensemble is exceeded, leading to reduced operational effectiveness. Automated support both in the processing of voluminous sensor data and sensor asset control can relieve the burden of human operators to support operation of larger ISR ensembles. In dynamic environments it is essential to react quickly to current information to avoid stale, sub-optimal plans. Our approach is to apply the principles of feedback control to ISR operations, "closing the loop" from the sensor collections through automated processing to ISR asset control. Previous work by the authors demonstrated non-myopic multiple platform trajectory control using a receding horizon controller in a closed feedback loop with a multiple hypothesis tracker applied to multi-target search and track simulation scenarios in the ground and space domains. This paper presents extensions in both size and scope of the previous work, demonstrating closed-loop control, involving both platform routing and sensor pointing, of a multisensor, multi-platform ISR ensemble tasked with providing situational awareness and performing search, track and classification of multiple moving ground targets in irregular warfare scenarios. The closed-loop ISR system is fullyrealized using distributed, asynchronous components that communicate over a network. The closed-loop ISR system has been exercised via a networked simulation test bed against a scenario in the Afghanistan theater implemented using high-fidelity terrain and imagery data. In addition, the system has been applied to space surveillance scenarios requiring tracking of space objects where current deliberative, manually intensive processes for managing sensor assets are insufficiently responsive. Simulation experiment results are presented. The algorithm to jointly optimize sensor schedules against search, track, and classify is based on recent work by Papageorgiou and Raykin on risk-based sensor management. It uses a risk-based objective function and attempts to minimize and balance the risks of misclassifying and losing track on an object. It supports the requirement to generate tasking for metric and feature data concurrently and synergistically, and account for both tracking accuracy and object characterization, jointly, in computing reward and cost for optimizing tasking decisions.

Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

2014-06-19

Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stablemore » information ratio.« less

Large Artery Atherosclerotic Occlusive Disease.

PubMed

Cole, John W

2017-02-01

Extracranial or intracranial large artery atherosclerosis is often identified as a potential etiologic cause for ischemic stroke and transient ischemic attack. Given the high prevalence of large artery atherosclerosis in the general population, determining whether an identified atherosclerotic lesion is truly the cause of a patient's symptomatology can be difficult. In all cases, optimally treating each patient to minimize future stroke risk is paramount. Extracranial or intracranial large artery atherosclerosis can be broadly compartmentalized into four distinct clinical scenarios based upon the individual patient's history, examination, and anatomic imaging findings: asymptomatic and symptomatic extracranial carotid stenosis, intracranial atherosclerosis, and extracranial vertebral artery atherosclerotic disease. This review provides a framework for clinicians evaluating and treating such patients. Intensive medical therapy achieves low rates of stroke and death in asymptomatic carotid stenosis. Evidence indicates that patients with severe symptomatic carotid stenosis should undergo carotid revascularization sooner rather than later and that the risk of stroke or death is lower using carotid endarterectomy than with carotid stenting. Specific to stenting, the risk of stroke or death is greatest among older patients and women. Continuous vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy is the mainstay for stroke prevention in the setting of intracranial and vertebral artery origin atherosclerosis. Lifelong vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy are the key elements to reduce future stroke risk in the setting of large artery atherosclerosis. When considering a revascularization procedure for carotid stenosis, patient demographics, comorbidities, and the periprocedural risks of stroke and death should be carefully considered.

Large Artery Atherosclerotic Occlusive Disease

PubMed Central

Cole, John W.

2017-01-01

ABSTRACT Purpose of Review: Extracranial or intracranial large artery atherosclerosis is often identified as a potential etiologic cause for ischemic stroke and transient ischemic attack. Given the high prevalence of large artery atherosclerosis in the general population, determining whether an identified atherosclerotic lesion is truly the cause of a patient’s symptomatology can be difficult. In all cases, optimally treating each patient to minimize future stroke risk is paramount. Extracranial or intracranial large artery atherosclerosis can be broadly compartmentalized into four distinct clinical scenarios based upon the individual patient’s history, examination, and anatomic imaging findings: asymptomatic and symptomatic extracranial carotid stenosis, intracranial atherosclerosis, and extracranial vertebral artery atherosclerotic disease. This review provides a framework for clinicians evaluating and treating such patients. Recent Findings: Intensive medical therapy achieves low rates of stroke and death in asymptomatic carotid stenosis. Evidence indicates that patients with severe symptomatic carotid stenosis should undergo carotid revascularization sooner rather than later and that the risk of stroke or death is lower using carotid endarterectomy than with carotid stenting. Specific to stenting, the risk of stroke or death is greatest among older patients and women. Continuous vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy is the mainstay for stroke prevention in the setting of intracranial and vertebral artery origin atherosclerosis. Summary: Lifelong vascular risk factor optimization via sustained behavioral modifications and intensive medical therapy are the key elements to reduce future stroke risk in the setting of large artery atherosclerosis. When considering a revascularization procedure for carotid stenosis, patient demographics, comorbidities, and the periprocedural risks of stroke and death should be carefully considered. PMID:28157748

Assessing the potential of economic instruments for managing drought risk at river basin scale

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, M.; Lopez-Nicolas, A.; Macian-Sorribes, H.

2015-12-01

Economic instruments work as incentives to adapt individual decisions to collectively agreed goals. Different types of economic instruments have been applied to manage water resources, such as water-related taxes and charges (water pricing, environmental taxes, etc.), subsidies, markets or voluntary agreements. Hydroeconomic models (HEM) provide useful insight on optimal strategies for coping with droughts by simultaneously analysing engineering, hydrology and economics of water resources management. We use HEMs for evaluating the potential of economic instruments on managing drought risk at river basin scale, considering three criteria for assessing drought risk: reliability, resilience and vulnerability. HEMs allow to calculate water scarcity costs as the economic losses due to water deliveries below the target demands, which can be used as a vulnerability descriptor of drought risk. Two generic hydroeconomic DSS tools, SIMGAMS and OPTIGAMS ( both programmed in GAMS) have been developed to evaluate water scarcity cost at river basin scale based on simulation and optimization approaches. The simulation tool SIMGAMS allocates water according to the system priorities and operating rules, and evaluate the scarcity costs using economic demand functions. The optimization tool allocates water resources for maximizing net benefits (minimizing total water scarcity plus operating cost of water use). SIMGAS allows to simulate incentive water pricing policies based on water availability in the system (scarcity pricing), while OPTIGAMS is used to simulate the effect of ideal water markets by economic optimization. These tools have been applied to the Jucar river system (Spain), highly regulated and with high share of water use for crop irrigation (greater than 80%), where water scarcity, irregular hydrology and groundwater overdraft cause droughts to have significant economic, social and environmental consequences. An econometric model was first used to explain the variation of the production value of irrigated agriculture during droughts, assessing revenue responses to varying crop prices and water availability. Hydroeconomic approaches were then used to show the potential of economic instruments in setting incentives for a more efficient management of water resources systems.

A systematic conservation planning approach to fire risk management in Natura 2000 sites.

PubMed

Foresta, Massimiliano; Carranza, Maria Laura; Garfì, Vittorio; Di Febbraro, Mirko; Marchetti, Marco; Loy, Anna

2016-10-01

A primary challenge in conservation biology is to preserve the most representative biodiversity while simultaneously optimizing the efforts associated with conservation. In Europe, the implementation of the Natura 2000 network requires protocols to recognize and map threats to biodiversity and to identify specific mitigation actions. We propose a systematic conservation planning approach to optimize management actions against specific threats based on two fundamental parameters: biodiversity values and threat pressure. We used the conservation planning software Marxan to optimize a fire management plan in a Natura 2000 coastal network in southern Italy. We address three primary questions: i) Which areas are at high fire risk? ii) Which areas are the most valuable for threatened biodiversity? iii) Which areas should receive priority risk-mitigation actions for the optimal effect?, iv) which fire-prevention actions are feasible in the management areas?. The biodiversity values for the Natura 2000 spatial units were derived from the distribution maps of 18 habitats and 89 vertebrate species of concern in Europe (Habitat Directive 92/43/EEC). The threat pressure map, defined as fire probability, was obtained from digital layers of fire risk and of fire frequency. Marxan settings were defined as follows: a) planning units of 40 × 40 m, b) conservation features defined as all habitats and vertebrate species of European concern occurring in the study area, c) conservation targets defined according with fire sensitivity and extinction risk of conservation features, and d) costs determined as the complement of fire probabilities. We identified 23 management areas in which to concentrate efforts for the optimal reduction of fire-induced effects. Because traditional fire prevention is not feasible for most of policy habitats included in the management areas, alternative prevention practices were identified that allows the conservation of the vegetation structure. The proposed approach has potential applications for multiple landscapes, threats and spatial scales and could be extended to other valuable natural areas, including protected areas. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Optimal distribution of borehole geophones for monitoring CO2-injection-induced seismicity

NASA Astrophysics Data System (ADS)

Huang, L.; Chen, T.; Foxall, W.; Wagoner, J. L.

2016-12-01

The U.S. DOE initiative, National Risk Assessment Partnership (NRAP), aims to develop quantitative risk assessment methodologies for carbon capture, utilization and storage (CCUS). As part of tasks of the Strategic Monitoring Group of NRAP, we develop a tool for optimal design of a borehole geophones distribution for monitoring CO2-injection-induced seismicity. The tool consists of a number of steps, including building a geophysical model for a given CO2 injection site, defining target monitoring regions within CO2-injection/migration zones, generating synthetic seismic data, giving acceptable uncertainties in input data, and determining the optimal distribution of borehole geophones. We use a synthetic geophysical model as an example to demonstrate the capability our new tool to design an optimal/cost-effective passive seismic monitoring network using borehole geophones. The model is built based on the geologic features found at the Kimberlina CCUS pilot site located in southern San Joaquin Valley, California. This tool can provide CCUS operators with a guideline for cost-effective microseismic monitoring of geologic carbon storage and utilization.

A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

PubMed

Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

2015-01-01

Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

Optimism, Cynical Hostility, Falls, and Fractures: The Women's Health Initiative Observational Study (WHI-OS).

PubMed

Cauley, Jane A; Smagula, Stephen F; Hovey, Kathleen M; Wactawski-Wende, Jean; Andrews, Christopher A; Crandall, Carolyn J; LeBoff, Meryl S; Li, Wenjun; Coday, Mace; Sattari, Maryam; Tindle, Hilary A

2017-02-01

Traits of optimism and cynical hostility are features of personality that could influence the risk of falls and fractures by influencing risk-taking behaviors, health behaviors, or inflammation. To test the hypothesis that personality influences falls and fracture risk, we studied 87,342 women enrolled in WHI-OS. Optimism was assessed by the Life Orientation Test-Revised and cynical hostility, the cynicism subscale of the Cook-Medley questionnaire. Higher scores indicate greater optimism and hostility. Optimism and hostility were correlated at r = -0. 31, p < 0.001. Annual self-report of falling ≥2 times in the past year was modeled using repeated measures logistic regression. Cox proportional hazards models were used for the fracture outcomes. We examined the risk of falls and fractures across the quartiles (Q) of optimism and hostility with tests for trends; Q1 formed the referent group. The average follow-up for fractures was 11.4 years and for falls was 7.6 years. In multivariable (MV)-adjusted models, women with the highest optimism scores (Q4) were 11% less likely to report ≥2 falls in the past year (odds ratio [OR] = 0.89; 95% confidence intervals [CI] 0.85-0.90). Women in Q4 for hostility had a 12% higher risk of ≥2 falls (OR = 1.12; 95% CI 1.07-1.17). Higher optimism scores were also associated with a 10% lower risk of fractures, but this association was attenuated in MV models. Women with the greatest hostility (Q4) had a modest increased risk of any fracture (MV-adjusted hazard ratio = 1. 05; 95% CI 1.01-1.09), but there was no association with specific fracture sites. In conclusion, optimism was independently associated with a decreased risk of ≥2 falls, and hostility with an increased risk of ≥2 falls, independent of traditional risk factors. The magnitude of the association was similar to aging 5 years. Whether interventions aimed at attitudes could reduce fall risks remains to be determined. © 2016 American Society for Bone and Mineral Research. © 2016 American Society for Bone and Mineral Research.

MeProRisk - a Joint Venture for Minimizing Risk in Geothermal Reservoir Development

NASA Astrophysics Data System (ADS)

Clauser, C.; Marquart, G.

2009-12-01

Exploration and development of geothermal reservoirs for the generation of electric energy involves high engineering and economic risks due to the need for 3-D geophysical surface surveys and deep boreholes. The MeProRisk project provides a strategy guideline for reducing these risks by combining cross-disciplinary information from different specialists: Scientists from three German universities and two private companies contribute with new methods in seismic modeling and interpretation, numerical reservoir simulation, estimation of petrophysical parameters, and 3-D visualization. The approach chosen in MeProRisk consists in considering prospecting and developing of geothermal reservoirs as an iterative process. A first conceptual model for fluid flow and heat transport simulation can be developed based on limited available initial information on geology and rock properties. In the next step, additional data is incorporated which is based on (a) new seismic interpretation methods designed for delineating fracture systems, (b) statistical studies on large numbers of rock samples for estimating reliable rock parameters, (c) in situ estimates of the hydraulic conductivity tensor. This results in a continuous refinement of the reservoir model where inverse modelling of fluid flow and heat transport allows infering the uncertainty and resolution of the model at each iteration step. This finally yields a calibrated reservoir model which may be used to direct further exploration by optimizing additional borehole locations, estimate the uncertainty of key operational and economic parameters, and optimize the long-term operation of a geothermal resrvoir.

Identification of effective screening strategies for cardiovascular disease prevention in a developing country: using cardiovascular risk-estimation and risk-reduction tools for policy recommendations.

PubMed

Selvarajah, Sharmini; Haniff, Jamaiyah; Kaur, Gurpreet; Guat Hiong, Tee; Bujang, Adam; Chee Cheong, Kee; Bots, Michiel L

2013-02-25

Recent increases in cardiovascular risk-factor prevalences have led to new national policy recommendations of universal screening for primary prevention of cardiovascular disease in Malaysia. This study assessed whether the current national policy recommendation of universal screening was optimal, by comparing the effectiveness and impact of various cardiovascular screening strategies. Data from a national population based survey of 24 270 participants aged 30 to 74 was used. Five screening strategies were modelled for the overall population and by gender; universal and targeted screening (four age cut-off points). Screening strategies were assessed based on the ability to detect high cardiovascular risk populations (effectiveness), incremental effectiveness, impact on cardiovascular event prevention and cost of screening. 26.7% (95% confidence limits 25.7, 27.7) were at high cardiovascular risk, men 34.7% (33.6, 35.8) and women 18.9% (17.8, 20). Universal screening identified all those at high-risk and resulted in one high-risk individual detected for every 3.7 people screened, with an estimated cost of USD60. However, universal screening resulted in screening an additional 7169 persons, with an incremental cost of USD115,033 for detection of one additional high-risk individual in comparison to targeted screening of those aged ≥35 years. The cost, incremental cost and impact of detection of high-risk individuals were more for women than men for all screening strategies. The impact of screening women aged ≥45 years was similar to universal screening in men. Targeted gender- and age-specific screening strategies would ensure more optimal utilisation of scarce resources compared to the current policy recommendations of universal screening.

Identification of effective screening strategies for cardiovascular disease prevention in a developing country: using cardiovascular risk-estimation and risk-reduction tools for policy recommendations

PubMed Central

2013-01-01

Background Recent increases in cardiovascular risk-factor prevalences have led to new national policy recommendations of universal screening for primary prevention of cardiovascular disease in Malaysia. This study assessed whether the current national policy recommendation of universal screening was optimal, by comparing the effectiveness and impact of various cardiovascular screening strategies. Methods Data from a national population based survey of 24 270 participants aged 30 to 74 was used. Five screening strategies were modelled for the overall population and by gender; universal and targeted screening (four age cut-off points). Screening strategies were assessed based on the ability to detect high cardiovascular risk populations (effectiveness), incremental effectiveness, impact on cardiovascular event prevention and cost of screening. Results 26.7% (95% confidence limits 25.7, 27.7) were at high cardiovascular risk, men 34.7% (33.6, 35.8) and women 18.9% (17.8, 20). Universal screening identified all those at high-risk and resulted in one high-risk individual detected for every 3.7 people screened, with an estimated cost of USD60. However, universal screening resulted in screening an additional 7169 persons, with an incremental cost of USD115,033 for detection of one additional high-risk individual in comparison to targeted screening of those aged ≥35 years. The cost, incremental cost and impact of detection of high-risk individuals were more for women than men for all screening strategies. The impact of screening women aged ≥45 years was similar to universal screening in men. Conclusions Targeted gender- and age-specific screening strategies would ensure more optimal utilisation of scarce resources compared to the current policy recommendations of universal screening. PMID:23442728

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorissen, BL; Giantsoudi, D; Unkelbach, J

Purpose: Cell survival experiments suggest that the relative biological effectiveness (RBE) of proton beams depends on linear energy transfer (LET), leading to higher RBE near the end of range. With intensity-modulated proton therapy (IMPT), multiple treatment plans that differ in the dose contribution per field may yield a similar physical dose distribution, but the RBE-weighted dose distribution may be disparate. RBE models currently do not have the required predictive power to be included in an optimization model due to the variations in experimental data. We propose an LET-based planning method that guides IMPT optimization models towards plans with reduced RBE-weightedmore » dose in surrounding organs at risk (OARs) compared to inverse planning based on physical dose alone. Methods: Optimization models for physical dose are extended with a term for dose times LET (doseLET). Monte Carlo code is used to generate the physical dose and doseLET distribution of each individual pencil beam. The method is demonstrated for an atypical meningioma patient where the target volume abuts the brainstem and partially overlaps with the optic nerve. Results: A reference plan optimized based on physical dose alone yields high doseLET values in parts of the brainstem and optic nerve. Minimizing doseLET in these critical structures as an additional planning goal reduces the risk of high RBE-weighted dose. The resulting treatment plan avoids the distal fall-off of the Bragg peaks for shaping the dose distribution in front of critical stuctures. The maximum dose in the OARs evaluated with RBE models from literature is reduced by 8–14\\% with our method compared to conventional planning. Conclusion: LET-based inverse planning for IMPT offers the ability to reduce the RBE-weighted dose in OARs without sacrificing target dose. This project was in part supported by NCI - U19 CA 21239.« less

Scaling range sizes to threats for robust predictions of risks to biodiversity.

PubMed

Keith, David A; Akçakaya, H Resit; Murray, Nicholas J

2018-04-01

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range-size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red-list assessments for decades, appropriate spatial scales of AOO for predicting risks of species' extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale-sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1-1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer-scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid-measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape-scale threats to species and ecosystems. © 2017 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Valuing hydrological alteration in multi-objective water resources management

NASA Astrophysics Data System (ADS)

Bizzi, Simone; Pianosi, Francesca; Soncini-Sessa, Rodolfo

2012-11-01

SummaryThe management of water through the impoundment of rivers by dams and reservoirs is necessary to support key human activities such as hydropower production, agriculture and flood risk mitigation. Advances in multi-objective optimization techniques and ever growing computing power make it possible to design reservoir operating policies that represent Pareto-optimal tradeoffs between multiple interests. On the one hand, such optimization methods can enhance performances of commonly targeted objectives (such as hydropower production or water supply), on the other hand they risk strongly penalizing all the interests not directly (i.e. mathematically) included in the optimization algorithm. The alteration of the downstream hydrological regime is a well established cause of ecological degradation and its evaluation and rehabilitation is commonly required by recent legislation (as the Water Framework Directive in Europe). However, it is rarely embedded in reservoir optimization routines and, even when explicitly considered, the criteria adopted for its evaluation are doubted and not commonly trusted, undermining the possibility of real implementation of environmentally friendly policies. The main challenges in defining and assessing hydrological alterations are: how to define a reference state (referencing); how to define criteria upon which to build mathematical indicators of alteration (measuring); and finally how to aggregate the indicators in a single evaluation index (valuing) that can serve as objective function in the optimization problem. This paper aims to address these issues by: (i) discussing the benefits and constrains of different approaches to referencing, measuring and valuing hydrological alteration; (ii) testing two alternative indices of hydrological alteration, one based on the established framework of Indicators of Hydrological Alteration (Richter et al., 1996), and one satisfying the mathematical properties required by widely used optimization methods based on dynamic programming; (iii) demonstrating and discussing these indices by application River Ticino, in Italy; (iv) providing a framework to effectively include hydrological alteration within reservoir operation optimization.

Improving Information Security Risk Management

ERIC Educational Resources Information Center

Singh, Anand

2009-01-01

manaOptimizing risk to information to protect the enterprise as well as to satisfy government and industry mandates is a core function of most information security departments. Risk management is the discipline that is focused on assessing, mitigating, monitoring and optimizing risks to information. Risk assessments and analyses are critical…

Robust optimization based upon statistical theory.

PubMed

Sobotta, B; Söhn, M; Alber, M

2010-08-01

Organ movement is still the biggest challenge in cancer treatment despite advances in online imaging. Due to the resulting geometric uncertainties, the delivered dose cannot be predicted precisely at treatment planning time. Consequently, all associated dose metrics (e.g., EUD and maxDose) are random variables with a patient-specific probability distribution. The method that the authors propose makes these distributions the basis of the optimization and evaluation process. The authors start from a model of motion derived from patient-specific imaging. On a multitude of geometry instances sampled from this model, a dose metric is evaluated. The resulting pdf of this dose metric is termed outcome distribution. The approach optimizes the shape of the outcome distribution based on its mean and variance. This is in contrast to the conventional optimization of a nominal value (e.g., PTV EUD) computed on a single geometry instance. The mean and variance allow for an estimate of the expected treatment outcome along with the residual uncertainty. Besides being applicable to the target, the proposed method also seamlessly includes the organs at risk (OARs). The likelihood that a given value of a metric is reached in the treatment is predicted quantitatively. This information reveals potential hazards that may occur during the course of the treatment, thus helping the expert to find the right balance between the risk of insufficient normal tissue sparing and the risk of insufficient tumor control. By feeding this information to the optimizer, outcome distributions can be obtained where the probability of exceeding a given OAR maximum and that of falling short of a given target goal can be minimized simultaneously. The method is applicable to any source of residual motion uncertainty in treatment delivery. Any model that quantifies organ movement and deformation in terms of probability distributions can be used as basis for the algorithm. Thus, it can generate dose distributions that are robust against interfraction and intrafraction motion alike, effectively removing the need for indiscriminate safety margins.

Convex reformulation of biologically-based multi-criteria intensity-modulated radiation therapy optimization including fractionation effects

NASA Astrophysics Data System (ADS)

Hoffmann, Aswin L.; den Hertog, Dick; Siem, Alex Y. D.; Kaanders, Johannes H. A. M.; Huizenga, Henk

2008-11-01

Finding fluence maps for intensity-modulated radiation therapy (IMRT) can be formulated as a multi-criteria optimization problem for which Pareto optimal treatment plans exist. To account for the dose-per-fraction effect of fractionated IMRT, it is desirable to exploit radiobiological treatment plan evaluation criteria based on the linear-quadratic (LQ) cell survival model as a means to balance the radiation benefits and risks in terms of biologic response. Unfortunately, the LQ-model-based radiobiological criteria are nonconvex functions, which make the optimization problem hard to solve. We apply the framework proposed by Romeijn et al (2004 Phys. Med. Biol. 49 1991-2013) to find transformations of LQ-model-based radiobiological functions and establish conditions under which transformed functions result in equivalent convex criteria that do not change the set of Pareto optimal treatment plans. The functions analysed are: the LQ-Poisson-based model for tumour control probability (TCP) with and without inter-patient heterogeneity in radiation sensitivity, the LQ-Poisson-based relative seriality s-model for normal tissue complication probability (NTCP), the equivalent uniform dose (EUD) under the LQ-Poisson model and the fractionation-corrected Probit-based model for NTCP according to Lyman, Kutcher and Burman. These functions differ from those analysed before in that they cannot be decomposed into elementary EUD or generalized-EUD functions. In addition, we show that applying increasing and concave transformations to the convexified functions is beneficial for the piecewise approximation of the Pareto efficient frontier.

Sequencing of disease-modifying therapies for relapsing-remitting multiple sclerosis: a theoretical approach to optimizing treatment.

PubMed

Grand'Maison, Francois; Yeung, Michael; Morrow, Sarah A; Lee, Liesly; Emond, Francois; Ward, Brian J; Laneuville, Pierre; Schecter, Robyn

2018-04-18

Multiple sclerosis (MS) is a chronic disease which usually begins in young adulthood and is a lifelong condition. Individuals with MS experience physical and cognitive disability resulting from inflammation and demyelination in the central nervous system. Over the past decade, several disease-modifying therapies (DMTs) have been approved for the management of relapsing-remitting MS (RRMS), which is the most prevalent phenotype. The chronic nature of the disease and the multiple treatment options make benefit-risk-based sequencing of therapy essential to ensure optimal care. The efficacy and short- and long-term risks of treatment differ for each DMT due to their different mechanism of action on the immune system. While transitioning between DMTs, in addition to immune system effects, factors such as age, disease duration and severity, disability status, monitoring requirements, preference for the route of administration, and family planning play an important role. Determining a treatment strategy is therefore challenging as it requires careful consideration of the differences in efficacy, safety and tolerability, while at the same time minimizing risks of immune modulation. In this review, we discuss a sequencing approach for treating RRMS, with importance given to the long-term risks and individual preference when devising a treatment plan. Evidence-based strategies to counter breakthrough disease are also addressed.

Portfolio optimization with mean-variance model

NASA Astrophysics Data System (ADS)

Hoe, Lam Weng; Siew, Lam Weng

2016-06-01

Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

A decision-making tool for exchange transfusions in infants with severe hyperbilirubinemia in resource-limited settings.

PubMed

Olusanya, B O; Iskander, I F; Slusher, T M; Wennberg, R P

2016-05-01

Late presentation and ineffective phototherapy account for excessive rates of avoidable exchange transfusions (ETs) in many low- and middle-income countries. Several system-based constraints sometimes limit the ability to provide timely ETs for all infants at risk of kernicterus, thus necessitating a treatment triage to optimize available resources. This article proposes a practical priority-setting model for term and near-term infants requiring ET after the first 48 h of life. The proposed model combines plasma/serum bilirubin estimation, clinical signs of acute bilirubin encephalopathy and neurotoxicity risk factors for predicting the risk of kernicterus based on available evidence in the literature.

Determining optimal gestational weight gain in the Korean population: a retrospective cohort study.

PubMed

Choi, Sae Kyung; Lee, Guisera; Kim, Yeon Hee; Park, In Yang; Ko, Hyun Sun; Shin, Jong Chul

2017-08-22

The World Health Organization (WHO) international body mass index (BMI) cut-off points defining pre-pregnancy BMI categories in the Institute of Medicine (IOM) guidelines are not directly applicable to Asians. We aimed to define the optimal gestational weight gain (GWG) for the Korean population based on Asia-specific BMI categories. Data from 2702 live singleton deliveries in three tertiary centers between 2010 and 2011 were analyzed retrospectively. A multivariable logistic regression analysis was conducted to determine the lowest aggregated risk of composite perinatal outcomes based on Asia-specific BMI categories. The perinatal outcomes included gestational hypertensive disorder, emergency cesarean section, and fetal size for gestational age. In each BMI category, the GWG value corresponding to the lowest aggregated risk was defined as the optimal GWG. Among the study population, 440 (16.3%) were underweight (BMI < 18.5), 1459 (54.0%) were normal weight (18.5 ≤ BMI < 23), 392 (14.5%) were overweight (23 ≤ BMI < 25) and 411 (15.2%) were obese (BMI ≥ 25). The optimal GWG by Asia-specific BMI category was 20.8 kg (range, 16.7 to 24.7) for underweight, 16.6 kg (11.5 to 21.5) for normal weight, 13.1 kg (8.0 to 17.7) for overweight, and 14.4 kg (7.5 to 21.9) for obese. Considerably higher and wider optimal GWG ranges than recommended by IOM are found in our study in order to avoid adverse perinatal outcomes. Revised IOM recommendations for GWG could be considered for Korean women according to Asian BMI categories. Further prospective studies are needed in order to determine the optimal GWG for the Korean population.

Defining Optimal Brain Health in Adults: A Presidential Advisory From the American Heart Association/American Stroke Association.

PubMed

Gorelick, Philip B; Furie, Karen L; Iadecola, Costantino; Smith, Eric E; Waddy, Salina P; Lloyd-Jones, Donald M; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W; Girgus, Meighan; Howard, Virginia J; Lazar, Ronald M; Seshadri, Sudha; Testai, Fernando D; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-10-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA's Life's Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m 2 ) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer's Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA's Life's Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA's Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention. © 2017 American Heart Association, Inc.

Defining Optimal Brain Health in Adults

PubMed Central

Gorelick, Philip B.; Furie, Karen L.; Iadecola, Costantino; Smith, Eric E.; Waddy, Salina P.; Lloyd-Jones, Donald M.; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W.; Girgus, Meighan; Howard, Virginia J.; Lazar, Ronald M.; Seshadri, Sudha; Testai, Fernando D.; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-01-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA’s Life’s Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m2) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer’s Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA’s Life’s Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA’s Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention. PMID:28883125

New algorithms for optimal reduction of technical risks

NASA Astrophysics Data System (ADS)

Todinov, M. T.

2013-06-01

The article features exact algorithms for reduction of technical risk by (1) optimal allocation of resources in the case where the total potential loss from several sources of risk is a sum of the potential losses from the individual sources; (2) optimal allocation of resources to achieve a maximum reduction of system failure; and (3) making an optimal choice among competing risky prospects. The article demonstrates that the number of activities in a risky prospect is a key consideration in selecting the risky prospect. As a result, the maximum expected profit criterion, widely used for making risk decisions, is fundamentally flawed, because it does not consider the impact of the number of risk-reward activities in the risky prospects. A popular view, that if a single risk-reward bet with positive expected profit is unacceptable then a sequence of such identical risk-reward bets is also unacceptable, has been analysed and proved incorrect.

SU-E-T-109: An Investigation of Including Variable Relative Biological Effectiveness in Intensity Modulated Proton Therapy Planning Optimization for Head and Neck Cancer Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, W; Zaghian, M; Lim, G

2015-06-15

Purpose: The current practice of considering the relative biological effectiveness (RBE) of protons in intensity modulated proton therapy (IMPT) planning is to use a generic RBE value of 1.1. However, RBE is indeed a variable depending on the dose per fraction, the linear energy transfer, tissue parameters, etc. In this study, we investigate the impact of using variable RBE based optimization (vRBE-OPT) on IMPT dose distributions compared by conventional fixed RBE based optimization (fRBE-OPT). Methods: Proton plans of three head and neck cancer patients were included for our study. In order to calculate variable RBE, tissue specific parameters were obtainedmore » from the literature and dose averaged LET values were calculated by Monte Carlo simulations. Biological effects were calculated using the linear quadratic model and they were utilized in the variable RBE based optimization. We used a Polak-Ribiere conjugate gradient algorithm to solve the model. In fixed RBE based optimization, we used conventional physical dose optimization to optimize doses weighted by 1.1. IMPT plans for each patient were optimized by both methods (vRBE-OPT and fRBE-OPT). Both variable and fixed RBE weighted dose distributions were calculated for both methods and compared by dosimetric measures. Results: The variable RBE weighted dose distributions were more homogenous within the targets, compared with the fixed RBE weighted dose distributions for the plans created by vRBE-OPT. We observed that there were noticeable deviations between variable and fixed RBE weighted dose distributions if the plan were optimized by fRBE-OPT. For organs at risk sparing, dose distributions from both methods were comparable. Conclusion: Biological dose based optimization rather than conventional physical dose based optimization in IMPT planning may bring benefit in improved tumor control when evaluating biologically equivalent dose, without sacrificing OAR sparing, for head and neck cancer patients. The research is supported in part by National Institutes of Health Grant No. 2U19CA021239-35.« less

Risk analysis of heat recovery steam generator with semi quantitative risk based inspection API 581

NASA Astrophysics Data System (ADS)

Prayogo, Galang Sandy; Haryadi, Gunawan Dwi; Ismail, Rifky; Kim, Seon Jin

2016-04-01

Corrosion is a major problem that most often occurs in the power plant. Heat recovery steam generator (HRSG) is an equipment that has a high risk to the power plant. The impact of corrosion damage causing HRSG power plant stops operating. Furthermore, it could be threaten the safety of employees. The Risk Based Inspection (RBI) guidelines by the American Petroleum Institute (API) 58 has been used to risk analysis in the HRSG 1. By using this methodology, the risk that caused by unexpected failure as a function of the probability and consequence of failure can be estimated. This paper presented a case study relating to the risk analysis in the HRSG, starting with a summary of the basic principles and procedures of risk assessment and applying corrosion RBI for process industries. The risk level of each HRSG equipment were analyzed: HP superheater has a medium high risk (4C), HP evaporator has a medium-high risk (4C), and the HP economizer has a medium risk (3C). The results of the risk assessment using semi-quantitative method of standard API 581 based on the existing equipment at medium risk. In the fact, there is no critical problem in the equipment components. Damage mechanisms were prominent throughout the equipment is thinning mechanism. The evaluation of the risk approach was done with the aim of reducing risk by optimizing the risk assessment activities.

Water shortage risk assessment considering large-scale regional transfers: a copula-based uncertainty case study in Lunan, China.

PubMed

Gao, Xueping; Liu, Yinzhu; Sun, Bowen

2018-06-05

The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mouton, S.; Ledoux, Y.; Teissandier, D.

A key challenge for the future is to reduce drastically the human impact on the environment. In the aeronautic field, this challenge aims at optimizing the design of the aircraft to decrease the global mass. This reduction leads to the optimization of every part constitutive of the plane. This operation is even more delicate when the used material is composite material. In this case, it is necessary to find a compromise between the strength, the mass and the manufacturing cost of the component. Due to these different kinds of design constraints it is necessary to assist engineer with decision supportmore » system to determine feasible solutions. In this paper, an approach is proposed based on the coupling of the different key characteristics of the design process and on the consideration of the failure risk of the component. The originality of this work is that the manufacturing deviations due to the RTM process are integrated in the simulation of the assembly process. Two kinds of deviations are identified: volume impregnation (injection phase of RTM process) and geometrical deviations (curing and cooling phases). The quantification of these deviations and the related failure risk calculation is based on finite element simulations (Pam RTM registered and Samcef registered softwares). The use of genetic algorithm allows to estimate the impact of the design choices and their consequences on the failure risk of the component. The main focus of the paper is the optimization of tool design. In the framework of decision support systems, the failure risk calculation is used for making the comparison of possible industrialization alternatives. It is proposed to apply this method on a particular part of the airplane structure: a spar unit made of carbon fiber/epoxy composite.« less

The effect of decentralized behavioral decision making on system-level risk.

PubMed

Kaivanto, Kim

2014-12-01

Certain classes of system-level risk depend partly on decentralized lay decision making. For instance, an organization's network security risk depends partly on its employees' responses to phishing attacks. On a larger scale, the risk within a financial system depends partly on households' responses to mortgage sales pitches. Behavioral economics shows that lay decisionmakers typically depart in systematic ways from the normative rationality of expected utility (EU), and instead display heuristics and biases as captured in the more descriptively accurate prospect theory (PT). In turn, psychological studies show that successful deception ploys eschew direct logical argumentation and instead employ peripheral-route persuasion, manipulation of visceral emotions, urgency, and familiar contextual cues. The detection of phishing emails and inappropriate mortgage contracts may be framed as a binary classification task. Signal detection theory (SDT) offers the standard normative solution, formulated as an optimal cutoff threshold, for distinguishing between good/bad emails or mortgages. In this article, we extend SDT behaviorally by rederiving the optimal cutoff threshold under PT. Furthermore, we incorporate the psychology of deception into determination of SDT's discriminability parameter. With the neo-additive probability weighting function, the optimal cutoff threshold under PT is rendered unique under well-behaved sampling distributions, tractable in computation, and transparent in interpretation. The PT-based cutoff threshold is (i) independent of loss aversion and (ii) more conservative than the classical SDT cutoff threshold. Independently of any possible misalignment between individual-level and system-level misclassification costs, decentralized behavioral decisionmakers are biased toward underdetection, and system-level risk is consequently greater than in analyses predicated upon normative rationality. © 2014 Society for Risk Analysis.

Assessing and managing breast cancer risk: clinicians' current practice and future needs.

PubMed

Collins, Ian M; Steel, Emma; Mann, G Bruce; Emery, Jon D; Bickerstaffe, Adrian; Trainer, Alison; Butow, Phyllis; Pirotta, Marie; Antoniou, Antonis C; Cuzick, Jack; Hopper, John; Phillips, Kelly-Anne; Keogh, Louise A

2014-10-01

Decision support tools for the assessment and management of breast cancer risk may improve uptake of prevention strategies. End-user input in the design of such tools is critical to increase clinical use. Before developing such a computerized tool, we examined clinicians' practice and future needs. Twelve breast surgeons, 12 primary care physicians and 5 practice nurses participated in 4 focus groups. These were recorded, coded, and analyzed to identify key themes. Participants identified difficulties assessing risk, including a lack of available tools to standardize practice. Most expressed confidence identifying women at potentially high risk, but not moderate risk. Participants felt a tool could especially reassure young women at average risk. Desirable features included: evidence-based, accessible (e.g. web-based), and displaying absolute (not relative) risks in multiple formats. The potential to create anxiety was a concern. Development of future tools should address these issues to optimize translation of knowledge into clinical practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

Consensus and controversy regarding osteoporosis in the pediatric population.

PubMed

Bachrach, Laura Keyes

2007-09-01

To review current consensus and controversy surrounding the diagnosis and treatment of osteoporosis in childhood and adolescence. The medical literature was reviewed with emphasis on the importance of early skeletal health, risk factors for bone fragility, and the diagnosis and management of children at risk for osteoporosis. Childhood and adolescence are critical periods for optimizing bone growth and mineral accrual. Bone strength is determined by bone size, geometry, quality, and mass-variables that are influenced by genetic factors, activity, nutrition, and hormones. For children with genetic skeletal disorders or chronic disease, bone growth and mineral accrual may be compromised, increasing the lifetime risk of osteoporosis. The goal for the clinician is to identify children at greatest risk for future fragility fracture. Bone densitometry and turnover markers are challenging to interpret in children. Prevention and treatment of bone fragility in children are less well established than in adults. Optimizing nutrition and activity may not restore bone health, but the drug armamentarium is limited. Sex steroid replacement has not proven effective in restoring bone mass in patients with anorexia nervosa or exercise-associated amenorrhea. Bisphosphonates can increase bone mass and may reduce bone pain and fractures, most convincingly in patients with osteogenesis imperfecta. Further studies are needed to establish the safety, efficacy, and optimal drug, duration, and dosage in pediatric patients. Bone health during the first 2 decades contributes to the lifetime risk of osteoporosis. Further research is needed to develop evidence-based recommendations for the diagnosis and treatment of osteoporosis in childhood.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Unkelbach, Jan, E-mail: junkelbach@mgh.harvard.edu; Botas, Pablo; Faculty of Physics, Ruprecht-Karls-Universität Heidelberg, Heidelberg

Purpose: We describe a treatment plan optimization method for intensity modulated proton therapy (IMPT) that avoids high values of linear energy transfer (LET) in critical structures located within or near the target volume while limiting degradation of the best possible physical dose distribution. Methods and Materials: To allow fast optimization based on dose and LET, a GPU-based Monte Carlo code was extended to provide dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dosemore » objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of LET and physical dose (LET×D). To first approximation, LET×D represents a measure of the additional biological dose that is caused by high LET. Results: The method is effective for treatments where serial critical structures with maximum dose constraints are located within or near the target. We report on 5 patients with intracranial tumors (high-grade meningiomas, base-of-skull chordomas, ependymomas) in whom the target volume overlaps with the brainstem and optic structures. In all cases, high LET×D in critical structures could be avoided while minimally compromising physical dose planning objectives. Conclusion: LET-based reoptimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and relative biological effectiveness (RBE)-based planning. The method makes IMPT treatments safer by mitigating a potentially increased risk of side effects resulting from elevated RBE of proton beams near the end of range.« less

Association of Lipid Accumulation Product with Cardio-Metabolic Risk Factors in Postmenopausal Women.

PubMed

Namazi Shabestari, Alireza; Asadi, Mojgan; Jouyandeh, Zahra; Qorbani, Mostafa; Kelishadi, Roya

2016-06-01

The lipid accumulation product is a novel, safe and inexpensive index of central lipid over accumulation based on waist circumference and fasting concentration of circulating triglycerides. This study was designed to investigate the ability of lipid accumulation product to predict Cardio-metabolic risk factors in postmenopausal women. In this Cross-sectional study, 264 postmenopausal women by using convenience sampling method were selected from menopause clinic in Tehran. Cardio-metabolic risk factors were measured, and lipid accumulation product (waist-58×triglycerides [nmol/L]) was calculated. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was estimated by ROC (Receiver-operating characteristic) curve analysis. Metabolic syndrome was diagnosed in 41.2% of subjects. Optimal cut-off point of lipid accumulation product for predicting metabolic syndrome was 47.63 (sensitivity:75%; specificity:77.9%). High lipid accumulation product increases risk of all Cardio-metabolic risk factors except overweight, high Total Cholesterol, high Low Density Lipoprotein Cholesterol and high Fasting Blood Sugar in postmenopausal women. Our findings show that lipid accumulation product is associated with metabolic syndrome and some Cardio-metabolic risk factors Also lipid accumulation product may have been a useful tool for predicting cardiovascular disease and metabolic syndrome risk in postmenopausal women.

The Role of Text Messaging in Cardiovascular Risk Factor Optimization.

PubMed

Klimis, Harry; Khan, Mohammad Ehsan; Kok, Cindy; Chow, Clara K

2017-01-01

Many cases of CVD may be avoidable through lowering behavioural risk factors such as smoking and physical inactivity. Mobile health (mHealth) provides a novel opportunity to deliver cardiovascular prevention programs in a format that is potentially scalable. Here, we provide an overview of text messaging-based mHealth interventions in cardiovascular prevention. Text messaging-based interventions appear effective on a range of behavioural risk factors and can effect change on multiple risk factors-e.g. smoking, weight, blood pressure-simultaneously. For many texting studies, there are challenges in interpretation as many texting interventions are part of larger complex interventions making it difficult to determine the benefits of the separate components. Whilst there is evidence for text messaging improving cardiovascular risk factor levels in the short-term, future studies are needed to examine the durability of these effects and whether they can be translated to improvements in clinical care and outcomes.

Fetal and neonatal alloimmune thrombocytopenia: evidence based antenatal and postnatal management strategies.

PubMed

Winkelhorst, Dian; Oepkes, Dick; Lopriore, Enrico

2017-08-01

Fetal and neonatal alloimmune thrombocytopenia (FNAIT) is a relatively rare but potentially lethal disease, leading to severe bleeding complications in 1 in 11.000 newborns. It is the leading cause of thrombocytopenia in healthy term-born neonates. Areas covered: This review summarizes the antenatal as well as postnatal treatment, thus creating a complete overview of all possible management strategies for FNAIT. Expert commentary: The optimal antenatal therapy in order to prevent bleeding complications in pregnancies complicated by FNAIT is non-invasive treatment with weekly intravenous immunoglobulin (IVIG). Based on risk stratification, weekly doses of IVIG of 0.5 or 1.0g/kg should be administered started early in the second in high risk cases or at the end of the second trimester in low risk cases. The optimal postnatal treatment depends on the platelet count and the clinical condition of the newborn. Prompt administration of compatible platelet transfusion is the first treatment of choice in case of severe thrombocytopenia or active bleeding. In case matched platelets are not directly available, random platelets can also be administered initially to gain time until matched platelets are available. In case of persistent thrombocytopenia despite transfusions, IVIG 1.0-2.0g/kg can be administered.

Active animal health surveillance in European Union Member States: gaps and opportunities.

PubMed

Bisdorff, B; Schauer, B; Taylor, N; Rodríguez-Prieto, V; Comin, A; Brouwer, A; Dórea, F; Drewe, J; Hoinville, L; Lindberg, A; Martinez Avilés, M; Martínez-López, B; Peyre, M; Pinto Ferreira, J; Rushton, J; VAN Schaik, G; Stärk, K D C; Staubach, C; Vicente-Rubiano, M; Witteveen, G; Pfeiffer, D; Häsler, B

2017-03-01

Animal health surveillance enables the detection and control of animal diseases including zoonoses. Under the EU-FP7 project RISKSUR, a survey was conducted in 11 EU Member States and Switzerland to describe active surveillance components in 2011 managed by the public or private sector and identify gaps and opportunities. Information was collected about hazard, target population, geographical focus, legal obligation, management, surveillance design, risk-based sampling, and multi-hazard surveillance. Two countries were excluded due to incompleteness of data. Most of the 664 components targeted cattle (26·7%), pigs (17·5%) or poultry (16·0%). The most common surveillance objectives were demonstrating freedom from disease (43·8%) and case detection (26·8%). Over half of components applied risk-based sampling (57·1%), but mainly focused on a single population stratum (targeted risk-based) rather than differentiating between risk levels of different strata (stratified risk-based). About a third of components were multi-hazard (37·3%). Both risk-based sampling and multi-hazard surveillance were used more frequently in privately funded components. The study identified several gaps (e.g. lack of systematic documentation, inconsistent application of terminology) and opportunities (e.g. stratified risk-based sampling). The greater flexibility provided by the new EU Animal Health Law means that systematic evaluation of surveillance alternatives will be required to optimize cost-effectiveness.

A diffusion-based approach to stochastic individual growth and energy budget, with consequences to life-history optimization and population dynamics.

PubMed

Filin, I

2009-06-01

Using diffusion processes, I model stochastic individual growth, given exogenous hazards and starvation risk. By maximizing survival to final size, optimal life histories (e.g. switching size for habitat/dietary shift) are determined by two ratios: mean growth rate over growth variance (diffusion coefficient) and mortality rate over mean growth rate; all are size dependent. For example, switching size decreases with either ratio, if both are positive. I provide examples and compare with previous work on risk-sensitive foraging and the energy-predation trade-off. I then decompose individual size into reversibly and irreversibly growing components, e.g. reserves and structure. I provide a general expression for optimal structural growth, when reserves grow stochastically. I conclude that increased growth variance of reserves delays structural growth (raises threshold size for its commencement) but may eventually lead to larger structures. The effect depends on whether the structural trait is related to foraging or defence. Implications for population dynamics are discussed.

A methodology to assess the economic impact of power storage technologies.

PubMed

El-Ghandour, Laila; Johnson, Timothy C

2017-08-13

We present a methodology for assessing the economic impact of power storage technologies. The methodology is founded on classical approaches to the optimal stopping of stochastic processes but involves an innovation that circumvents the need to, ex ante , identify the form of a driving process and works directly on observed data, avoiding model risks. Power storage is regarded as a complement to the intermittent output of renewable energy generators and is therefore important in contributing to the reduction of carbon-intensive power generation. Our aim is to present a methodology suitable for use by policy makers that is simple to maintain, adaptable to different technologies and easy to interpret. The methodology has benefits over current techniques and is able to value, by identifying a viable optimal operational strategy, a conceived storage facility based on compressed air technology operating in the UK.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Optimism and death: predicting the course and consequences of depression trajectories in response to heart attack.

PubMed

Galatzer-Levy, Isaac R; Bonanno, George A

2014-12-01

The course of depression in relation to myocardial infarction (MI), commonly known as heart attack, and the consequences for mortality are not well characterized. Further, optimism may predict both the effects of MI on depression as well as mortality secondary to MI. In the current study, we utilized a large population-based prospective sample of older adults (N=2,147) to identify heterogeneous trajectories of depression from 6 years prior to their first-reported MI to 4 years after. Findings indicated that individuals were at significantly increased risk for mortality when depression emerged after their first-reported MI, compared with resilient individuals who had no significant post-MI elevation in depression symptomatology. Individuals with chronic depression and those demonstrating pre-event depression followed by recovery after MI were not at increased risk. Further, optimism, measured before MI, prospectively differentiated all depressed individuals from participants who were resilient. © The Author(s) 2014.

Carotid stenosis - basing treatment on individual patients' needs. Optimal medical therapy alone or accompanied by stenting or endarterectomy.

PubMed

Langhoff, Ralf

2018-01-01

Though carotid artery stenosis is a known origin of stroke, risk assessment and treatment modality are not yet satisfactorily established. Guideline updates according to latest evidence are expected shortly. Current clinical weakness concerns in particular the identification of "at-risk" patients. Beside the symptomatic status and the degree of stenosis, further signs of unstable plaque on carotid and cerebral imaging should be considered. Moreover, medical and endovascular therapy are continuously improving. Randomized trials and meta-analyses have shown similar long-term results for protected carotid artery stenting and endarterectomy. However, endovascular revascularization was associated with an increased 30-day rate of minor strokes. Newly developed embolic protection devices could possibly compensate for this disadvantage. Furthermore, high-level optimal medical therapy alone is currently being evaluated comparatively. We assume that a comprehensive evaluation of plaque vulnerability, serious consideration of advanced embolic protection, and more space for optimal medical therapy alone according to latest evidence, will benefit patients with carotid stenosis.

SU-F-T-195: Systematic Constraining of Contralateral Parotid Gland Led to Improved Dosimetric Outcomes for Multi-Field Optimization with Scanning Beam Proton Therapy: Promising Results From a Pilot Study in Patients with Base of Tongue Carcinoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, R; Liu, A; Poenisch, F

Purpose: Treatment planning for Intensity Modulated Proton Therapy (IMPT) for head and neck cancer is time-consuming due to the large number of organs-at-risk (OAR) to be considered. As there are many competing objectives and also wide range of acceptable OAR constraints, the final approved plan may not be most optimal for the given structures. We evaluated the dose reduction to the contralateral parotid by implementing standardized constraints during optimization for scanning beam proton therapy planning. Methods: Twenty-four (24) consecutive patients previously treated for base of tongue carcinoma were retrospectively selected. The doses were 70Gy, 63Gy and 57Gy (SIB in 33more » fractions) for high-, intermediate-, and standard-risk clinical target volumes (CTV), respectively; the treatment included bilateral neck. Scanning beams using MFO with standardized bilateral anterior oblique and PA fields were applied. New plans where then developed and optimized by employing additional contralateral parotid constraints at multiple defined dose levels. Using a step-wise iterative process, the volume-based constraints at each level were then further reduced until known target coverages were compromised. The newly developed plans were then compared to the original clinically approved plans using paired student t-testing. Results: All 24 newly optimized treatment plans maintained initial plan quality as compared to the approved plans, and the 98% prescription dose coverage to the CTV’s were not compromised. Representative DVH comparison is shown in FIGURE 1. The contralateral parotid doses were reduced at all levels of interest when systematic constraints were applied to V10, V20, V30 and V40Gy (All P<0.0001; TABLE 1). Overall, the mean contralateral parotid doses were reduced by 2.26 Gy on average, a ∼13% relative improvement. Conclusion: Applying systematic and volume-based contralateral parotid constraints for IMPT planning significantly reduced the dose at all dosimetric levels for patients with base of tongue cancer.« less

A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels.

PubMed

Xu, Ming; Jiao, Yan; Li, Xiaoming; Cao, Qingfeng; Wang, Xiaoyang

2015-01-01

This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations.

A Multi-Period Optimization Model for Service Providers Using Online Reservation Systems: An Application to Hotels

PubMed Central

Xu, Ming; Jiao, Yan; Li, Xiaoming; Cao, Qingfeng; Wang, Xiaoyang

2015-01-01

This paper presents a multi-period optimization model for high margin and zero salvage products in online distribution channels with classifying customers based on number of products required. Taking hotel customers as an example, one is regular customers who reserve rooms for one day, and the other is long term stay (LTS) customers who reserve rooms for a number of days. LTS may guarantee a specific amount of demand and generate opportunity income for a certain number of periods, meanwhile with risk of punishment incurred by overselling. By developing an operational optimization model and exploring the effects of parameters on optimal decisions, we suggest that service providers should make decisions based on the types of customers, number of products required, and duration of multi-period to reduce the loss of reputation and obtain more profit; at the same time, multi-period buying customers should buy products early. Finally, the paper conducts a numerical experiment, and the results are consistent with prevailing situations. PMID:26147663

Optimization of black-box models with uncertain climatic inputs—Application to sunflower ideotype design

PubMed Central

Picheny, Victor; Trépos, Ronan; Casadebaig, Pierre

2017-01-01

Accounting for the interannual climatic variations is a well-known issue for simulation-based studies of environmental systems. It often requires intensive sampling (e.g., averaging the simulation outputs over many climatic series), which hinders many sequential processes, in particular optimization algorithms. We propose here an approach based on a subset selection in a large basis of climatic series, using an ad-hoc similarity function and clustering. A non-parametric reconstruction technique is introduced to estimate accurately the distribution of the output of interest using only the subset sampling. The proposed strategy is non-intrusive and generic (i.e. transposable to most models with climatic data inputs), and can be combined to most “off-the-shelf” optimization solvers. We apply our approach to sunflower ideotype design using the crop model SUNFLO. The underlying optimization problem is formulated as a multi-objective one to account for risk-aversion. Our approach achieves good performances even for limited computational budgets, outperforming significantly standard strategies. PMID:28542198

Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kouri, Drew Philip; Surowiec, Thomas M.

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new riskmore » measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.« less

Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization

DOE PAGES

Kouri, Drew Philip; Surowiec, Thomas M.

2018-06-05

Uncertainty is ubiquitous in virtually all engineering applications, and, for such problems, it is inadequate to simulate the underlying physics without quantifying the uncertainty in unknown or random inputs, boundary and initial conditions, and modeling assumptions. Here in this paper, we introduce a general framework for analyzing risk-averse optimization problems constrained by partial differential equations (PDEs). In particular, we postulate conditions on the random variable objective function as well as the PDE solution that guarantee existence of minimizers. Furthermore, we derive optimality conditions and apply our results to the control of an environmental contaminant. Lastly, we introduce a new riskmore » measure, called the conditional entropic risk, that fuses desirable properties from both the conditional value-at-risk and the entropic risk measures.« less

A variable structure fuzzy neural network model of squamous dysplasia and esophageal squamous cell carcinoma based on a global chaotic optimization algorithm.

PubMed

Moghtadaei, Motahareh; Hashemi Golpayegani, Mohammad Reza; Malekzadeh, Reza

2013-02-07

Identification of squamous dysplasia and esophageal squamous cell carcinoma (ESCC) is of great importance in prevention of cancer incidence. Computer aided algorithms can be very useful for identification of people with higher risks of squamous dysplasia, and ESCC. Such method can limit the clinical screenings to people with higher risks. Different regression methods have been used to predict ESCC and dysplasia. In this paper, a Fuzzy Neural Network (FNN) model is selected for ESCC and dysplasia prediction. The inputs to the classifier are the risk factors. Since the relation between risk factors in the tumor system has a complex nonlinear behavior, in comparison to most of ordinary data, the cost function of its model can have more local optimums. Thus the need for global optimization methods is more highlighted. The proposed method in this paper is a Chaotic Optimization Algorithm (COA) proceeding by the common Error Back Propagation (EBP) local method. Since the model has many parameters, we use a strategy to reduce the dependency among parameters caused by the chaotic series generator. This dependency was not considered in the previous COA methods. The algorithm is compared with logistic regression model as the latest successful methods of ESCC and dysplasia prediction. The results represent a more precise prediction with less mean and variance of error. Copyright © 2012 Elsevier Ltd. All rights reserved.

Planning Risk-Based SQC Schedules for Bracketed Operation of Continuous Production Analyzers.

PubMed

Westgard, James O; Bayat, Hassan; Westgard, Sten A

2018-02-01

To minimize patient risk, "bracketed" statistical quality control (SQC) is recommended in the new CLSI guidelines for SQC (C24-Ed4). Bracketed SQC requires that a QC event both precedes and follows (brackets) a group of patient samples. In optimizing a QC schedule, the frequency of QC or run size becomes an important planning consideration to maintain quality and also facilitate responsive reporting of results from continuous operation of high production analytic systems. Different plans for optimizing a bracketed SQC schedule were investigated on the basis of Parvin's model for patient risk and CLSI C24-Ed4's recommendations for establishing QC schedules. A Sigma-metric run size nomogram was used to evaluate different QC schedules for processes of different sigma performance. For high Sigma performance, an effective SQC approach is to employ a multistage QC procedure utilizing a "startup" design at the beginning of production and a "monitor" design periodically throughout production. Example QC schedules are illustrated for applications with measurement procedures having 6-σ, 5-σ, and 4-σ performance. Continuous production analyzers that demonstrate high σ performance can be effectively controlled with multistage SQC designs that employ a startup QC event followed by periodic monitoring or bracketing QC events. Such designs can be optimized to minimize the risk of harm to patients. © 2017 American Association for Clinical Chemistry.

Impact of stakeholders influence, geographic level and risk perception on strategic decisions in simulated foot and mouth disease epizootics in France.

PubMed

Marsot, Maud; Rautureau, Séverine; Dufour, Barbara; Durand, Benoit

2014-01-01

Comparison of control strategies against animal infectious diseases allows determining optimal strategies according to their epidemiological and/or economic impacts. However, in real life, the choice of a control strategy does not always obey a pure economic or epidemiological rationality. The objective of this study was to analyze the choice of a foot and mouth disease (FMD) control strategy as a decision-making process in which the decision-maker is influenced by several stakeholders (government, agro-food industries, public opinion). For each of these, an indicator of epizootic impact was quantified to compare seven control strategies. We then determined how, in France, the optimal control strategy varied according to the relative weights of stakeholders and to the perception of risk by the decision-maker (risk-neutral/risk-averse). When the scope of decision was national, whatever their perception of risk and the stakeholders' weights, decision-makers chose a strategy based on vaccination. This consensus concealed marked differences between regions, which were connected with the regional breeding characteristics. Vaccination-based strategies were predominant in regions with dense cattle and swine populations, and in regions with a dense population of small ruminants, combined with a medium density of cattle and swine. These differences between regions suggested that control strategies could be usefully adapted to local breeding conditions. We then analyzed the feasibility of adaptive decision-making processes depending on the date and place where the epizootic starts, or on the evolution of the epizootic over time. The initial conditions always explained at least half of the variance of impacts, the remaining variance being attributed to the variability of epizootics evolution. However, the first weeks of this evolution explained a large part of the impacts variability. Although the predictive value of the initial conditions for determining the optimal strategy was weak, adaptive strategies changing dynamically according to the evolution of the epizootic appeared feasible.

Risk assessment and optimization (ALARA) analysis for the environmental remediation of Brookhaven National Laboratory`s hazardous waste management facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dionne, B.J.; Morris, S.C. III; Baum, J.W.

1998-01-01

The Department of Energy`s (DOE) Office of Environment, Safety, and Health (EH) sought examples of risk-based approaches to environmental restoration to include in their guidance for DOE nuclear facilities. Extensive measurements of radiological contamination in soil and ground water have been made at Brookhaven National Laboratory`s Hazardous Waste Management Facility (HWMF) as part of a Comprehensive Environmental Response, Compensation and Liability Act (CERCLA) remediation process. This provided an ideal opportunity for a case study. This report provides a risk assessment and an {open_quotes}As Low as Reasonably Achievable{close_quotes} (ALARA) analysis for use at other DOE nuclear facilities as an example ofmore » a risk-based decision technique. This document contains the Appendices for the report.« less

Irrigation, risk aversion, and water right priority under water supply uncertainty

NASA Astrophysics Data System (ADS)

Li, Man; Xu, Wenchao; Rosegrant, Mark W.

2017-09-01

This paper explores the impacts of a water right's allocative priority—as an indicator of farmers' risk-bearing ability—on land irrigation under water supply uncertainty. We develop and use an economic model to simulate farmers' land irrigation decision and associated economic returns in eastern Idaho. Results indicate that the optimal acreage of land irrigated increases with water right priority when hydroclimate risk exhibits a negatively skewed or right-truncated distribution. Simulation results suggest that prior appropriation enables senior water rights holders to allocate a higher proportion of their land to irrigation, 6 times as much as junior rights holders do, creating a gap in the annual expected net revenue reaching up to 141.4 acre-1 or 55,800 per farm between the two groups. The optimal irrigated acreage, expected net revenue, and shadow value of a water right's priority are subject to substantial changes under a changing climate in the future, where temporal variation in water supply risks significantly affects the profitability of agricultural land use under the priority-based water sharing mechanism.

Irrigation, risk aversion, and water right priority under water supply uncertainty.

PubMed

Li, Man; Xu, Wenchao; Rosegrant, Mark W

2017-09-01

This paper explores the impacts of a water right's allocative priority-as an indicator of farmers' risk-bearing ability-on land irrigation under water supply uncertainty. We develop and use an economic model to simulate farmers' land irrigation decision and associated economic returns in eastern Idaho. Results indicate that the optimal acreage of land irrigated increases with water right priority when hydroclimate risk exhibits a negatively skewed or right-truncated distribution. Simulation results suggest that prior appropriation enables senior water rights holders to allocate a higher proportion of their land to irrigation, 6 times as much as junior rights holders do, creating a gap in the annual expected net revenue reaching up to $141.4 acre -1 or $55,800 per farm between the two groups. The optimal irrigated acreage, expected net revenue, and shadow value of a water right's priority are subject to substantial changes under a changing climate in the future, where temporal variation in water supply risks significantly affects the profitability of agricultural land use under the priority-based water sharing mechanism.

Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method.

PubMed

Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan

2017-01-01

Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantifying pathogen risks associated with potable reuse: A risk assessment case study for Cryptosporidium.

PubMed

Amoueyan, Erfaneh; Ahmad, Sajjad; Eisenberg, Joseph N S; Pecson, Brian; Gerrity, Daniel

2017-08-01

This study evaluated the reliability and equivalency of three different potable reuse paradigms: (1) surface water augmentation via de facto reuse with conventional wastewater treatment; (2) surface water augmentation via planned indirect potable reuse (IPR) with ultrafiltration, pre-ozone, biological activated carbon (BAC), and post-ozone; and (3) direct potable reuse (DPR) with ultrafiltration, ozone, BAC, and UV disinfection. A quantitative microbial risk assessment (QMRA) was performed to (1) quantify the risk of infection from Cryptosporidium oocysts; (2) compare the risks associated with different potable reuse systems under optimal and sub-optimal conditions; and (3) identify critical model/operational parameters based on sensitivity analyses. The annual risks of infection associated with the de facto and planned IPR systems were generally consistent with those of conventional drinking water systems [mean of (9.4 ± 0.3) × 10 -5 to (4.5 ± 0.1) × 10 -4 ], while DPR was clearly superior [mean of (6.1 ± 67) × 10 -9 during sub-optimal operation]. Because the advanced treatment train in the planned IPR system was highly effective in reducing Cryptosporidium concentrations, the associated risks were generally dominated by the pathogen loading already present in the surface water. As a result, risks generally decreased with higher recycled water contributions (RWCs). Advanced treatment failures were generally inconsequential either due to the robustness of the advanced treatment train (i.e., DPR) or resiliency provided by the environmental buffer (i.e., planned IPR). Storage time in the environmental buffer was important for the de facto reuse system, and the model indicated a critical storage time of approximately 105 days. Storage times shorter than the critical value resulted in significant increases in risk. The conclusions from this study can be used to inform regulatory decision making and aid in the development of design or operational criteria for IPR and DPR systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk and Resilience in Pediatric Chronic Pain: Exploring the Protective Role of Optimism.

PubMed

Cousins, Laura A; Cohen, Lindsey L; Venable, Claudia

2015-10-01

Fear of pain and pain catastrophizing are prominent risk factors for pediatric chronic pain-related maladjustment. Although resilience has largely been ignored in the pediatric pain literature, prior research suggests that optimism might benefit youth and can be learned. We applied an adult chronic pain risk-resilience model to examine the interplay of risk factors and optimism on functioning outcomes in youth with chronic pain. Participants included 58 children and adolescents (8-17 years) attending a chronic pain clinic and their parents. Participants completed measures of fear of pain, pain catastrophizing, optimism, disability, and quality of life. Consistent with the literature, pain intensity, fear of pain, and catastrophizing predicted functioning. Optimism was a unique predictor of quality of life, and optimism contributed to better functioning by minimizing pain-related fear and catastrophizing. Optimism might be protective and offset the negative influence of fear of pain and catastrophizing on pain-related functioning. © The Author 2014. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Combined and Relative Effect Levels of Perceived Risk, Knowledge, Optimism, Pessimism, and Social Trust on Anxiety among Inhabitants Concerning Living on Heavy Metal Contaminated Soil

PubMed Central

Tang, Zhongjun; Guo, Zengli; Zhou, Li; Xue, Shengguo; Zhu, Qinfeng; Zhu, Huike

2016-01-01

This research aims at combined and relative effect levels on anxiety of: (1) perceived risk, knowledge, optimism, pessimism, and social trust; and (2) four sub-variables of social trust among inhabitants concerning living on heavy metal contaminated soil. On the basis of survey data from 499 Chinese respondents, results suggest that perceived risk, pessimism, optimism, and social trust have individual, significant, and direct effects on anxiety, while knowledge does not. Knowledge has significant, combined, and interactive effects on anxiety together with social trust and pessimism, respectively, but does not with perceived risk and optimism. Social trust, perceived risk, pessimism, knowledge, and optimism have significantly combined effects on anxiety; the five variables as a whole have stronger predictive values than each one individually. Anxiety is influenced firstly by social trust and secondly by perceived risk, pessimism, knowledge, and optimism. Each of four sub-variables of social trust has an individual, significant, and negative effect on anxiety. When introducing four sub-variables into one model, trust in social organizations and in the government have significantly combined effects on anxiety, while trust in experts and in friends and relatives do not; anxiety is influenced firstly by trust in social organization, and secondly by trust in the government. PMID:27827866

Combined and Relative Effect Levels of Perceived Risk, Knowledge, Optimism, Pessimism, and Social Trust on Anxiety among Inhabitants Concerning Living on Heavy Metal Contaminated Soil.

PubMed

Tang, Zhongjun; Guo, Zengli; Zhou, Li; Xue, Shengguo; Zhu, Qinfeng; Zhu, Huike

2016-11-02

This research aims at combined and relative effect levels on anxiety of: (1) perceived risk, knowledge, optimism, pessimism, and social trust; and (2) four sub-variables of social trust among inhabitants concerning living on heavy metal contaminated soil. On the basis of survey data from 499 Chinese respondents, results suggest that perceived risk, pessimism, optimism, and social trust have individual, significant, and direct effects on anxiety, while knowledge does not. Knowledge has significant, combined, and interactive effects on anxiety together with social trust and pessimism, respectively, but does not with perceived risk and optimism. Social trust, perceived risk, pessimism, knowledge, and optimism have significantly combined effects on anxiety; the five variables as a whole have stronger predictive values than each one individually. Anxiety is influenced firstly by social trust and secondly by perceived risk, pessimism, knowledge, and optimism. Each of four sub-variables of social trust has an individual, significant, and negative effect on anxiety. When introducing four sub-variables into one model, trust in social organizations and in the government have significantly combined effects on anxiety, while trust in experts and in friends and relatives do not; anxiety is influenced firstly by trust in social organization, and secondly by trust in the government.

Prediabetes: A high-risk state for developing diabetes

PubMed Central

Tabák, Adam G.; Herder, Christian; Rathmann, Wolfgang; Brunner, Eric J.; Kivimäki, Mika

2013-01-01

Summary Prediabetes (or “intermediate hyperglycaemia”), based on glycaemic parameters above normal but below diabetes thresholds is a high risk state for diabetes with an annualized conversion rate of 5%–10%; with similar proportion converting back to normoglycaemia. The prevalence of prediabetes is increasing worldwide and it is projected that >470 million people will have prediabetes in 2030. Prediabetes is associated with the simultaneous presence of insulin resistance and β-cell dysfunction, abnormalities that start before glucose changes are detectable. Observational evidence shows associations of prediabetes with early forms of nephropathy, chronic kidney disease, small fibre neuropathy, diabetic retinopathy, and increased risk of macrovascular disease. Multifactorial risk scores could optimize the estimation of diabetes risk using non-invasive parameters and blood-based metabolic traits in addition to glycaemic values. For prediabetic individuals, lifestyle modification is the cornerstone of diabetes prevention with evidence of a 40%–70% relative risk reduction. Accumulating data also suggests potential benefits from pharmacotherapy. PMID:22683128

Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.

A global airport-based risk model for the spread of dengue infection via the air transport network.

PubMed

Gardner, Lauren; Sarkar, Sahotra

2013-01-01

The number of travel-acquired dengue infections has seen a consistent global rise over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue has contributed to a rise in the number of dengue cases in both areas of endemicity and elsewhere. This paper reports results from a network-based risk assessment model which uses international passenger travel volumes, travel routes, travel distances, regional populations, and predictive species distribution models (for the two vector species, Aedes aegypti and Aedes albopictus) to quantify the relative risk posed by each airport in importing passengers with travel-acquired dengue infections. Two risk attributes are evaluated: (i) the risk posed by through traffic at each stopover airport and (ii) the risk posed by incoming travelers to each destination airport. The model results prioritize optimal locations (i.e., airports) for targeted dengue surveillance. The model is easily extendible to other vector-borne diseases.

A Global Airport-Based Risk Model for the Spread of Dengue Infection via the Air Transport Network

PubMed Central

Gardner, Lauren; Sarkar, Sahotra

2013-01-01

The number of travel-acquired dengue infections has seen a consistent global rise over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue has contributed to a rise in the number of dengue cases in both areas of endemicity and elsewhere. This paper reports results from a network-based risk assessment model which uses international passenger travel volumes, travel routes, travel distances, regional populations, and predictive species distribution models (for the two vector species, Aedes aegypti and Aedes albopictus) to quantify the relative risk posed by each airport in importing passengers with travel-acquired dengue infections. Two risk attributes are evaluated: (i) the risk posed by through traffic at each stopover airport and (ii) the risk posed by incoming travelers to each destination airport. The model results prioritize optimal locations (i.e., airports) for targeted dengue surveillance. The model is easily extendible to other vector-borne diseases. PMID:24009672

Breast Cancer Screening in an Era of Personalized Regimens

PubMed Central

Onega, Tracy; Beaber, Elisabeth F.; Sprague, Brian L.; Barlow, William E.; Haas, Jennifer S.; Tosteson, Anna N.A.; Schnall, Mitchell D.; Armstrong, Katrina; Schapira, Marilyn M.; Geller, Berta; Weaver, Donald L.; Conant, Emily F.

2014-01-01

Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women’s health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for “overdiagnosis,” and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a “1-size-fits-all” guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women’s risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform. PMID:24830599

Risk analysis of heat recovery steam generator with semi quantitative risk based inspection API 581

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prayogo, Galang Sandy, E-mail: gasandylang@live.com; Haryadi, Gunawan Dwi; Ismail, Rifky

Corrosion is a major problem that most often occurs in the power plant. Heat recovery steam generator (HRSG) is an equipment that has a high risk to the power plant. The impact of corrosion damage causing HRSG power plant stops operating. Furthermore, it could be threaten the safety of employees. The Risk Based Inspection (RBI) guidelines by the American Petroleum Institute (API) 58 has been used to risk analysis in the HRSG 1. By using this methodology, the risk that caused by unexpected failure as a function of the probability and consequence of failure can be estimated. This paper presentedmore » a case study relating to the risk analysis in the HRSG, starting with a summary of the basic principles and procedures of risk assessment and applying corrosion RBI for process industries. The risk level of each HRSG equipment were analyzed: HP superheater has a medium high risk (4C), HP evaporator has a medium-high risk (4C), and the HP economizer has a medium risk (3C). The results of the risk assessment using semi-quantitative method of standard API 581 based on the existing equipment at medium risk. In the fact, there is no critical problem in the equipment components. Damage mechanisms were prominent throughout the equipment is thinning mechanism. The evaluation of the risk approach was done with the aim of reducing risk by optimizing the risk assessment activities.« less

Tooth Whitening: What We Now Know

PubMed Central

Carey, Clifton M.

2014-01-01

Declarative Title Current research about tooth whitening shows that it is safe and effective when manufacturer’s protocol is followed, yet there are risks of which the profession and users should be aware. This update provides a summary of current research and assessment of the safety and efficacy of tooth whitening regimens. Background Tooth whitening has become one of the most frequently requested dental procedures by the public. The public has come to demand whiter, more perfect smiles and in response many choices for tooth whitening have been made available. These include home-based products such as toothpastes, gels, and films, as well as in-office based systems where products containing highly concentrated bleaching agents are applied under professional supervision. The profession and public have been aware of certain risks related to tooth whitening such as increased tooth sensitivity and gingival irritation. New research has shown that there are other risks such as tooth surface roughening and softening, increased potential for demineralization, degradation of dental restorations, and unacceptable color change of dental restorations. The new research is also focused on optimizing whitening procedures to reduce tooth sensitivity and to increase the persistence of the whitening. Methods Current reports in the literature are reviewed that are related to the use of peroxide based whitening methods. These reports include in vitro studies for method optimization and mechanism as well as clinical studies on effects of various whitening regimens. Conclusions When manufacturer’s instructions are followed, hydrogen peroxide and carbamide peroxide based tooth whitening is safe and effective. Patients should be informed of the risks associated with tooth whitening and instructed on identification of adverse occurrences so that they may seek professional help asneeded. PMID:24929591

Evaluating Monitoring Strategies to Detect Precipitation-Induced Microbial Contamination Events in Karstic Springs Used for Drinking Water

PubMed Central

Besmer, Michael D.; Hammes, Frederik; Sigrist, Jürg A.; Ort, Christoph

2017-01-01

Monitoring of microbial drinking water quality is a key component for ensuring safety and understanding risk, but conventional monitoring strategies are typically based on low sampling frequencies (e.g., quarterly or monthly). This is of concern because many drinking water sources, such as karstic springs are often subject to changes in bacterial concentrations on much shorter time scales (e.g., hours to days), for example after precipitation events. Microbial contamination events are crucial from a risk assessment perspective and should therefore be targeted by monitoring strategies to establish both the frequency of their occurrence and the magnitude of bacterial peak concentrations. In this study we used monitoring data from two specific karstic springs. We assessed the performance of conventional monitoring based on historical records and tested a number of alternative strategies based on a high-resolution data set of bacterial concentrations in spring water collected with online flow cytometry (FCM). We quantified the effect of increasing sampling frequency and found that for the specific case studied, at least bi-weekly sampling would be needed to detect precipitation events with a probability of >90%. We then proposed an optimized monitoring strategy with three targeted samples per event, triggered by precipitation measurements. This approach is more effective and efficient than simply increasing overall sampling frequency. It would enable the water utility to (1) analyze any relevant event and (2) limit median underestimation of peak concentrations to approximately 10%. We conclude with a generalized perspective on sampling optimization and argue that the assessment of short-term dynamics causing microbial peak loads initially requires increased sampling/analysis efforts, but can be optimized subsequently to account for limited resources. This offers water utilities and public health authorities systematic ways to evaluate and optimize their current monitoring strategies. PMID:29213255

Evaluating Monitoring Strategies to Detect Precipitation-Induced Microbial Contamination Events in Karstic Springs Used for Drinking Water.

PubMed

Besmer, Michael D; Hammes, Frederik; Sigrist, Jürg A; Ort, Christoph

2017-01-01

Monitoring of microbial drinking water quality is a key component for ensuring safety and understanding risk, but conventional monitoring strategies are typically based on low sampling frequencies (e.g., quarterly or monthly). This is of concern because many drinking water sources, such as karstic springs are often subject to changes in bacterial concentrations on much shorter time scales (e.g., hours to days), for example after precipitation events. Microbial contamination events are crucial from a risk assessment perspective and should therefore be targeted by monitoring strategies to establish both the frequency of their occurrence and the magnitude of bacterial peak concentrations. In this study we used monitoring data from two specific karstic springs. We assessed the performance of conventional monitoring based on historical records and tested a number of alternative strategies based on a high-resolution data set of bacterial concentrations in spring water collected with online flow cytometry (FCM). We quantified the effect of increasing sampling frequency and found that for the specific case studied, at least bi-weekly sampling would be needed to detect precipitation events with a probability of >90%. We then proposed an optimized monitoring strategy with three targeted samples per event, triggered by precipitation measurements. This approach is more effective and efficient than simply increasing overall sampling frequency. It would enable the water utility to (1) analyze any relevant event and (2) limit median underestimation of peak concentrations to approximately 10%. We conclude with a generalized perspective on sampling optimization and argue that the assessment of short-term dynamics causing microbial peak loads initially requires increased sampling/analysis efforts, but can be optimized subsequently to account for limited resources. This offers water utilities and public health authorities systematic ways to evaluate and optimize their current monitoring strategies.

Uncertainty analysis for effluent trading planning using a Bayesian estimation-based simulation-optimization modeling approach.

PubMed

Zhang, J L; Li, Y P; Huang, G H; Baetz, B W; Liu, J

2017-06-01

In this study, a Bayesian estimation-based simulation-optimization modeling approach (BESMA) is developed for identifying effluent trading strategies. BESMA incorporates nutrient fate modeling with soil and water assessment tool (SWAT), Bayesian estimation, and probabilistic-possibilistic interval programming with fuzzy random coefficients (PPI-FRC) within a general framework. Based on the water quality protocols provided by SWAT, posterior distributions of parameters can be analyzed through Bayesian estimation; stochastic characteristic of nutrient loading can be investigated which provides the inputs for the decision making. PPI-FRC can address multiple uncertainties in the form of intervals with fuzzy random boundaries and the associated system risk through incorporating the concept of possibility and necessity measures. The possibility and necessity measures are suitable for optimistic and pessimistic decision making, respectively. BESMA is applied to a real case of effluent trading planning in the Xiangxihe watershed, China. A number of decision alternatives can be obtained under different trading ratios and treatment rates. The results can not only facilitate identification of optimal effluent-trading schemes, but also gain insight into the effects of trading ratio and treatment rate on decision making. The results also reveal that decision maker's preference towards risk would affect decision alternatives on trading scheme as well as system benefit. Compared with the conventional optimization methods, it is proved that BESMA is advantageous in (i) dealing with multiple uncertainties associated with randomness and fuzziness in effluent-trading planning within a multi-source, multi-reach and multi-period context; (ii) reflecting uncertainties existing in nutrient transport behaviors to improve the accuracy in water quality prediction; and (iii) supporting pessimistic and optimistic decision making for effluent trading as well as promoting diversity of decision alternatives. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incorporating Equipment Condition Assessment in Risk Monitors for Advanced Small Modular Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coble, Jamie B.; Coles, Garill A.; Meyer, Ryan M.

2013-10-01

Advanced small modular reactors (aSMRs) can complement the current fleet of large light-water reactors in the USA for baseload and peak demand power production and process heat applications (e.g., water desalination, shale oil extraction, hydrogen production). The day-to-day costs of aSMRs are expected to be dominated by operations and maintenance (O&M); however, the effect of diverse operating missions and unit modularity on O&M is not fully understood. These costs could potentially be reduced by optimized scheduling, with risk-informed scheduling of maintenance, repair, and replacement of equipment. Currently, most nuclear power plants have a “living” probabilistic risk assessment (PRA), which reflectsmore » the as-operated, as-modified plant and combine event probabilities with population-based probability of failure (POF) for key components. “Risk monitors” extend the PRA by incorporating the actual and dynamic plant configuration (equipment availability, operating regime, environmental conditions, etc.) into risk assessment. In fact, PRAs are more integrated into plant management in today’s nuclear power plants than at any other time in the history of nuclear power. However, population-based POF curves are still used to populate fault trees; this approach neglects the time-varying condition of equipment that is relied on during standard and non-standard configurations. Equipment condition monitoring techniques can be used to estimate the component POF. Incorporating this unit-specific estimate of POF in the risk monitor can provide a more accurate estimate of risk in different operating and maintenance configurations. This enhanced risk assessment will be especially important for aSMRs that have advanced component designs, which don’t have an available operating history to draw from, and often use passive design features, which present challenges to PRA. This paper presents the requirements and technical gaps for developing a framework to integrate unit-specific estimates of POF into risk monitors, resulting in enhanced risk monitors that support optimized operation and maintenance of aSMRs.« less

SU-E-T-214: Intensity Modulated Proton Therapy (IMPT) Based On Passively Scattered Protons and Multi-Leaf Collimation: Prototype TPS and Dosimetry Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez-Parcerisa, D; Carabe-Fernandez, A

2014-06-01

Purpose. Intensity-modulated proton therapy is usually implemented with multi-field optimization of pencil-beam scanning (PBS) proton fields. However, at the view of the experience with photon-IMRT, proton facilities equipped with double-scattering (DS) delivery and multi-leaf collimation (MLC) could produce highly conformal dose distributions (and possibly eliminate the need for patient-specific compensators) with a clever use of their MLC field shaping, provided that an optimal inverse TPS is developed. Methods. A prototype TPS was developed in MATLAB. The dose calculation process was based on a fluence-dose algorithm on an adaptive divergent grid. A database of dose kernels was precalculated in order tomore » allow for fast variations of the field range and modulation during optimization. The inverse planning process was based on the adaptive simulated annealing approach, with direct aperture optimization of the MLC leaves. A dosimetry study was performed on a phantom formed by three concentrical semicylinders separated by 5 mm, of which the inner-most and outer-most were regarded as organs at risk (OARs), and the middle one as the PTV. We chose a concave target (which is not treatable with conventional DS fields) to show the potential of our technique. The optimizer was configured to minimize the mean dose to the OARs while keeping a good coverage of the target. Results. The plan produced by the prototype TPS achieved a conformity index of 1.34, with the mean doses to the OARs below 78% of the prescribed dose. This Result is hardly achievable with traditional conformal DS technique with compensators, and it compares to what can be obtained with PBS. Conclusion. It is certainly feasible to produce IMPT fields with MLC passive scattering fields. With a fully developed treatment planning system, the produced plans can be superior to traditional DS plans in terms of plan conformity and dose to organs at risk.« less

Cost-Effectiveness of Screening Individuals With Cystic Fibrosis for Colorectal Cancer.

PubMed

Gini, Andrea; Zauber, Ann G; Cenin, Dayna R; Omidvari, Amir-Houshang; Hempstead, Sarah E; Fink, Aliza K; Lowenfels, Albert B; Lansdorp-Vogelaar, Iris

2017-12-27

Individuals with cystic fibrosis are at increased risk of colorectal cancer (CRC) compared to the general population, and risk is higher among those who received an organ transplant. We performed a cost-effectiveness analysis to determine optimal CRC screening strategies for patients with cystic fibrosis. We adjusted the existing Microsimulation Screening Analysis-Colon microsimulation model to reflect increased CRC risk and lower life expectancy in patients with cystic fibrosis. Modeling was performed separately for individuals who never received an organ transplant and patients who had received an organ transplant. We modeled 76 colonoscopy screening strategies that varied the age range and screening interval. The optimal screening strategy was determined based on a willingness to pay threshold of $100,000 per life-year gained. Sensitivity and supplementary analyses were performed, including fecal immunochemical test (FIT) as an alternative test, earlier ages of transplantation, and increased rates of colonoscopy complications, to assess whether optimal screening strategies would change. Colonoscopy every 5 years, starting at age 40 years, was the optimal colonoscopy strategy for patients with cystic fibrosis who never received an organ transplant; this strategy prevented 79% of deaths from CRC. Among patients with cystic fibrosis who had received an organ transplant, optimal colonoscopy screening should start at an age of 30 or 35 years, depending on the patient's age at time of transplantation. Annual FIT screening was predicted to be cost-effective for patients with cystic fibrosis. However, the level of accuracy of the FIT in population is not clear. Using a Microsimulation Screening Analysis-Colon microsimulation model, we found screening of patients with cystic fibrosis for CRC to be cost-effective. Due to the higher risk in these patients for CRC, screening should start at an earlier age with a shorter screening interval. The findings of this study (especially those on FIT screening) may be limited by restricted evidence available for patients with cystic fibrosis. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Cost Effectiveness of Screening Individuals With Cystic Fibrosis for Colorectal Cancer.

PubMed

Gini, Andrea; Zauber, Ann G; Cenin, Dayna R; Omidvari, Amir-Houshang; Hempstead, Sarah E; Fink, Aliza K; Lowenfels, Albert B; Lansdorp-Vogelaar, Iris

2018-02-01

Individuals with cystic fibrosis are at increased risk of colorectal cancer (CRC) compared with the general population, and risk is higher among those who received an organ transplant. We performed a cost-effectiveness analysis to determine optimal CRC screening strategies for patients with cystic fibrosis. We adjusted the existing Microsimulation Screening Analysis-Colon model to reflect increased CRC risk and lower life expectancy in patients with cystic fibrosis. Modeling was performed separately for individuals who never received an organ transplant and patients who had received an organ transplant. We modeled 76 colonoscopy screening strategies that varied the age range and screening interval. The optimal screening strategy was determined based on a willingness to pay threshold of $100,000 per life-year gained. Sensitivity and supplementary analyses were performed, including fecal immunochemical test (FIT) as an alternative test, earlier ages of transplantation, and increased rates of colonoscopy complications, to assess if optimal screening strategies would change. Colonoscopy every 5 years, starting at an age of 40 years, was the optimal colonoscopy strategy for patients with cystic fibrosis who never received an organ transplant; this strategy prevented 79% of deaths from CRC. Among patients with cystic fibrosis who had received an organ transplant, optimal colonoscopy screening should start at an age of 30 or 35 years, depending on the patient's age at time of transplantation. Annual FIT screening was predicted to be cost-effective for patients with cystic fibrosis. However, the level of accuracy of the FIT in this population is not clear. Using a Microsimulation Screening Analysis-Colon model, we found screening of patients with cystic fibrosis for CRC to be cost effective. Because of the higher risk of CRC in these patients, screening should start at an earlier age with a shorter screening interval. The findings of this study (especially those on FIT screening) may be limited by restricted evidence available for patients with cystic fibrosis. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

Minimal investment risk of a portfolio optimization problem with budget and investment concentration constraints

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-02-01

In the present paper, the minimal investment risk for a portfolio optimization problem with imposed budget and investment concentration constraints is considered using replica analysis. Since the minimal investment risk is influenced by the investment concentration constraint (as well as the budget constraint), it is intuitive that the minimal investment risk for the problem with an investment concentration constraint can be larger than that without the constraint (that is, with only the budget constraint). Moreover, a numerical experiment shows the effectiveness of our proposed analysis. In contrast, the standard operations research approach failed to identify accurately the minimal investment risk of the portfolio optimization problem.

Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management.

PubMed

Govindan, Kannan; Jafarian, Ahmad; Azbari, Mostafa E; Choi, Tsan-Ming

2016-08-01

In the big data era, systems reliability is critical to effective systems risk management. In this paper, a novel multiobjective approach, with hybridization of a known algorithm called NSGA-II and an adaptive population-based simulated annealing (APBSA) method is developed to solve the systems reliability optimization problems. In the first step, to create a good algorithm, we use a coevolutionary strategy. Since the proposed algorithm is very sensitive to parameter values, the response surface method is employed to estimate the appropriate parameters of the algorithm. Moreover, to examine the performance of our proposed approach, several test problems are generated, and the proposed hybrid algorithm and other commonly known approaches (i.e., MOGA, NRGA, and NSGA-II) are compared with respect to four performance measures: 1) mean ideal distance; 2) diversification metric; 3) percentage of domination; and 4) data envelopment analysis. The computational studies have shown that the proposed algorithm is an effective approach for systems reliability and risk management.

Evaluation of the performance of existing non-laboratory based cardiovascular risk assessment algorithms

PubMed Central

2013-01-01

Background The high burden and rising incidence of cardiovascular disease (CVD) in resource constrained countries necessitates implementation of robust and pragmatic primary and secondary prevention strategies. Many current CVD management guidelines recommend absolute cardiovascular (CV) risk assessment as a clinically sound guide to preventive and treatment strategies. Development of non-laboratory based cardiovascular risk assessment algorithms enable absolute risk assessment in resource constrained countries. The objective of this review is to evaluate the performance of existing non-laboratory based CV risk assessment algorithms using the benchmarks for clinically useful CV risk assessment algorithms outlined by Cooney and colleagues. Methods A literature search to identify non-laboratory based risk prediction algorithms was performed in MEDLINE, CINAHL, Ovid Premier Nursing Journals Plus, and PubMed databases. The identified algorithms were evaluated using the benchmarks for clinically useful cardiovascular risk assessment algorithms outlined by Cooney and colleagues. Results Five non-laboratory based CV risk assessment algorithms were identified. The Gaziano and Framingham algorithms met the criteria for appropriateness of statistical methods used to derive the algorithms and endpoints. The Swedish Consultation, Framingham and Gaziano algorithms demonstrated good discrimination in derivation datasets. Only the Gaziano algorithm was externally validated where it had optimal discrimination. The Gaziano and WHO algorithms had chart formats which made them simple and user friendly for clinical application. Conclusion Both the Gaziano and Framingham non-laboratory based algorithms met most of the criteria outlined by Cooney and colleagues. External validation of the algorithms in diverse samples is needed to ascertain their performance and applicability to different populations and to enhance clinicians’ confidence in them. PMID:24373202

Brachytherapy optimization using radiobiological-based planning for high dose rate and permanent implants for prostate cancer treatment

NASA Astrophysics Data System (ADS)

Seeley, Kaelyn; Cunha, J. Adam; Hong, Tae Min

2017-01-01

We discuss an improvement in brachytherapy--a prostate cancer treatment method that directly places radioactive seeds inside target cancerous regions--by optimizing the current standard for delivering dose. Currently, the seeds' spatiotemporal placement is determined by optimizing the dose based on a set of physical, user-defined constraints. One particular approach is the ``inverse planning'' algorithms that allow for tightly fit isodose lines around the target volumes in order to reduce dose to the patient's organs at risk. However, these dose distributions are typically computed assuming the same biological response to radiation for different types of tissues. In our work, we consider radiobiological parameters to account for the differences in the individual sensitivities and responses to radiation for tissues surrounding the target. Among the benefits are a more accurate toxicity rate and more coverage to target regions for planning high-dose-rate treatments as well as permanent implants.

Meta-Modeling-Based Groundwater Remediation Optimization under Flexibility in Environmental Standard.

PubMed

He, Li; Xu, Zongda; Fan, Xing; Li, Jing; Lu, Hongwei

2017-05-01

  This study develops a meta-modeling based mathematical programming approach with flexibility in environmental standards. It integrates numerical simulation, meta-modeling analysis, and fuzzy programming within a general framework. A set of models between remediation strategies and remediation performance can well guarantee the mitigation in computational efforts in the simulation and optimization process. In order to prevent the occurrence of over-optimistic and pessimistic optimization strategies, a high satisfaction level resulting from the implementation of a flexible standard can indicate the degree to which the environmental standard is satisfied. The proposed approach is applied to a naphthalene-contaminated site in China. Results show that a longer remediation period corresponds to a lower total pumping rate and a stringent risk standard implies a high total pumping rate. The wells located near or in the down-gradient direction to the contaminant sources have the most significant efficiency among all of remediation schemes.

Why 'Optimal' Payment for Healthcare Providers Can Never be Optimal Under Community Rating.

PubMed

Zweifel, Peter; Frech, H E

2016-02-01

This article extends the existing literature on optimal provider payment by accounting for consumer heterogeneity in preferences for health insurance and healthcare. This heterogeneity breaks down the separation of the relationship between providers and the health insurer and the relationship between consumers and the insurer. Both experimental and market evidence for a high degree of heterogeneity are presented. Given heterogeneity, a uniform policy fails to effectively control moral hazard, while incentives for risk selection created by community rating cannot be neutralized through risk adjustment. Consumer heterogeneity spills over into relationships with providers, such that a uniform contract with providers also cannot be optimal. The decisive condition for ensuring optimality of provider payment is to replace community rating (which violates the principle of marginal cost pricing) with risk rating of contributions combined with subsidization targeted at high risks with low incomes.

Health Coaching to Optimize Well-Being among Returning Veterans with Suicide Risk

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-16-1-0630 TITLE: Health Coaching to Optimize Well-Being among Returning Veterans with Suicide Risk PRINCIPAL INVESTIGATOR...Lauren M. Denneson, PhD CONTRACTING ORGANIZATION: Oregon Health & Science University Portland, OR 97239 REPORT DATE: October 2017 TYPE OF...COVERED (From - To) 15 Sept 2016 - 14 Sept 2017 4. TITLE AND SUBTITLE Health Coaching to Optimize Well-Being among Returning Veterans with Suicide Risk

Optimal BMI Cut-off Points for Prediction of Incident Diabetes in Chinese population.

PubMed

Ma, Hao; Wu, Xiaoyan; Guo, Xiaoyu; Yang, Jianjun; Ma, Xiaohui; Lv, Mengfan; Li, Ying

2018-05-26

The current BMI classifications have been established based on risk of obesity-related conditions, but not specifically on type 2 diabetes mellitus (T2DM). This study aimed to identify the optimal BMI cutoffs for assessing incident T2DM risk in Chinese population. The longitudinal study cohort consisted of 8,735 non-diabetic participants aged 20-74 years at baseline, with a mean follow-up period of 6.0 years. Body mass index (BMI), 2-h glucose of 75-g oral glucose tolerance test, and glycosylated hemoglobin were measured at baseline and follow-up survey. During the follow-up period, 825 participants were diagnosed with T2DM. In multivariable Cox regression analyses, adjusting for covariates, a strong positive association between BMI and incident T2DM was found among whole population, when stratified by age groups (20-39 years, 40-59 years, 60-74 years), the risk associations between BMI and incident T2DM decreased with increasing age-specific groups, and extinguished in the 60-74 age group (P-value of interaction<0.001). The optimal BMI cut-offs (kg/m 2 ) for predicting T2DM risk for men and women were 25.5 and 24.4 in the 20-39 age group, and 23.5 and 23.0 in the 40-59 age group, respectively. But no predictive performance was observed in the 60-74 age group in both sexes. Our results suggested that the performance of BMI in predicting T2DM risk was the best in younger age and decreased with age. Age- and sex-specific BMI cut-offs should be considered for T2DM risk stratification in Chinese population. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Optimal timing of vitamin K antagonist resumption after upper gastrointestinal bleeding. A risk modelling analysis.

PubMed

Majeed, Ammar; Wallvik, Niklas; Eriksson, Joakim; Höijer, Jonas; Bottai, Matteo; Holmström, Margareta; Schulman, Sam

2017-02-28

The optimal timing of vitamin K antagonists (VKAs) resumption after an upper gastrointestinal (GI) bleeding, in patients with continued indication for oral anticoagulation, is uncertain. We included consecutive cases of VKA-associated upper GI bleeding from three hospitals retrospectively. Data on the bleeding location, timing of VKA resumption, recurrent GI bleeding and thromboembolic events were collected. A model was constructed to evaluate the 'total risk', based on the sum of the cumulative rates of recurrent GI bleeding and thromboembolic events, depending on the timing of VKA resumption. A total of 121 (58 %) of 207 patients with VKA-associated upper GI bleeding were restarted on anticoagulation after a median (interquartile range) of one (0.2-3.4) week after the index bleeding. Restarting VKAs was associated with a reduced risk of thromboembolism (HR 0.19; 95 % CI, 0.07-0.55) and death (HR 0.61; 95 % CI, 0.39-0.94), but with an increased risk of recurrent GI bleeding (HR 2.5; 95 % CI, 1.4-4.5). The composite risk obtained from the combined statistical model of recurrent GI bleeding, and thromboembolism decreased if VKAs were resumed after three weeks and reached a nadir at six weeks after the index GI bleeding. On this background we will discuss how the disutility of the outcomes may influence the decision regarding timing of resumption. In conclusion, the optimal timing of VKA resumption after VKA-associated upper GI bleeding appears to be between 3-6 weeks after the index bleeding event but has to take into account the degree of thromboembolic risk, patient values and preferences.

[How I treat: from specialized pharmacology to drug therapy: a plea for an optimal educational program for rational therapeutics, from decision making to drug prescription].

PubMed

Scheen, A J

2000-09-01

Clinical pharmacology and therapeutics are two complementary disciplines which should lead the medical student, through an optimized training, to a rational prescription of drugs, ultimate and important step of the medical approach. Such a learning should occur progressively throughout the medical education, focusing, first, on the therapeutic reasoning ("why?") and, second, on the practical application leading to the prescription ("how?"). The medical student should learn the difficult task of integrating disease, drug and patient, in order to optimize the benefit/risk ratio, while being informed about new concepts such as "Evidence-Based Medicine" and pharmacoeconomics.

Duration of anti-resorptive therapy for osteoporosis.

PubMed

Adler, Robert A

2016-02-01

Osteoporotic fractures are common, and available medications reduce fracture risk by up to half. However, because the most commonly used drugs, bisphosphonates, have side effects that may be related to duration of therapy and because long-term efficacy has not been established, the optimal length of treatment has not been determined. Based on two long-term studies and extensive clinical experience, a plan is provided to treat patients at risk for 5 years with re-assessment every 2 years thereafter. Assessment tools are limited, but for each individual, the potential risks and benefits of continuing, discontinuing, re-instituting, or changing therapy can be estimated.

Benefit-Risk Assessment, Communication, and Evaluation (BRACE) throughout the life cycle of therapeutic products: overall perspective and role of the pharmacoepidemiologist.

PubMed

Radawski, Christine; Morrato, Elaine; Hornbuckle, Kenneth; Bahri, Priya; Smith, Meredith; Juhaeri, Juhaeri; Mol, Peter; Levitan, Bennett; Huang, Han-Yao; Coplan, Paul; Li, Hu

2015-12-01

Optimizing a therapeutic product's benefit-risk profile is an on-going process throughout the product's life cycle. Different, yet related, benefit-risk assessment strategies and frameworks are being developed by various regulatory agencies, industry groups, and stakeholders. This paper summarizes current best practices and discusses the role of the pharmacoepidemiologist in these activities, taking a life-cycle approach to integrated Benefit-Risk Assessment, Communication, and Evaluation (BRACE). A review of the medical and regulatory literature was performed for the following steps involved in therapeutic benefit-risk optimization: benefit-risk evidence generation; data integration and analysis; decision making; regulatory and policy decision making; benefit-risk communication and risk minimization; and evaluation. Feedback from International Society for Pharmacoepidemiology members was solicited on the role of the pharmacoepidemiologist. The case example of natalizumab is provided to illustrate the cyclic nature of the benefit-risk optimization process. No single, globally adopted benefit-risk assessment process exists. The BRACE heuristic offers a way to clarify research needs and to promote best practices in a cyclic and integrated manner and highlight the critical importance of cross-disciplinary input. Its approach focuses on the integration of BRACE activities for risk minimization and optimization of the benefit-risk profile. The activities defined in the BRACE heuristic contribute to the optimization of the benefit-risk profile of therapeutic products in the clinical world at both the patient and population health level. With interdisciplinary collaboration, pharmacoepidemiologists are well suited for bringing in methodology expertise, relevant research, and public health perspectives into the BRACE process. Copyright © 2015 John Wiley & Sons, Ltd.

Frontal, Striatal, and Medial Temporal Sensitivity to Value Distinguishes Risk-Taking from Risk-Aversive Older Adults during Decision Making.

PubMed

Goh, Joshua O S; Su, Yu-Shiang; Tang, Yong-Jheng; McCarrey, Anna C; Tereshchenko, Alexander; Elkins, Wendy; Resnick, Susan M

2016-12-07

Aging compromises the frontal, striatal, and medial temporal areas of the reward system, impeding accurate value representation and feedback processing critical for decision making. However, substantial variability characterizes age-related effects on the brain so that some older individuals evince clear neurocognitive declines whereas others are spared. Moreover, the functional correlates of normative individual differences in older-adult value-based decision making remain unclear. We performed a functional magnetic resonance imaging study in 173 human older adults during a lottery choice task in which costly to more desirable stakes were depicted using low to high expected values (EVs) of points. Across trials that varied in EVs, participants decided to accept or decline the offered stakes to maximize total accumulated points. We found that greater age was associated with less optimal decisions, accepting stakes when losses were likely and declining stakes when gains were likely, and was associated with increased frontal activity for costlier stakes. Critically, risk preferences varied substantially across older adults and neural sensitivity to EVs in the frontal, striatal, and medial temporal areas dissociated risk-aversive from risk-taking individuals. Specifically, risk-averters increased neural responses to increasing EVs as stakes became more desirable, whereas risk-takers increased neural responses with decreasing EV as stakes became more costly. Risk preference also modulated striatal responses during feedback with risk-takers showing more positive responses to gains compared with risk-averters. Our findings highlight the frontal, striatal, and medial temporal areas as key neural loci in which individual differences differentially affect value-based decision-making ability in older adults. Frontal, striatal, and medial temporal functions implicated in value-based decision processing of rewards and costs undergo substantial age-related changes. However, age effects on brain function and cognition differ across individuals. How this normative variation relates to older-adult value-based decision making is unclear. We found that although the ability make optimal decisions declines with age, there is still much individual variability in how this deterioration occurs. Critically, whereas risk-averters showed increased neural activity to increasingly valuable stakes in frontal, striatal, and medial temporal areas, risk-takers instead increased activity as stakes became more costly. Such distinct functional decision-making processing in these brain regions across normative older adults may reflect individual differences in susceptibility to age-related brain changes associated with incipient cognitive impairment. Copyright © 2016 the authors 0270-6474/16/3612498-12$15.00/0.

Policy tree optimization for adaptive management of water resources systems

NASA Astrophysics Data System (ADS)

Herman, Jonathan; Giuliani, Matteo

2017-04-01

Water resources systems must cope with irreducible uncertainty in supply and demand, requiring policy alternatives capable of adapting to a range of possible future scenarios. Recent studies have developed adaptive policies based on "signposts" or "tipping points" that suggest the need of updating the policy. However, there remains a need for a general method to optimize the choice of the signposts to be used and their threshold values. This work contributes a general framework and computational algorithm to design adaptive policies as a tree structure (i.e., a hierarchical set of logical rules) using a simulation-optimization approach based on genetic programming. Given a set of feature variables (e.g., reservoir level, inflow observations, inflow forecasts), the resulting policy defines both the optimal reservoir operations and the conditions under which such operations should be triggered. We demonstrate the approach using Folsom Reservoir (California) as a case study, in which operating policies must balance the risk of both floods and droughts. Numerical results show that the tree-based policies outperform the ones designed via Dynamic Programming. In addition, they display good adaptive capacity to the changing climate, successfully adapting the reservoir operations across a large set of uncertain climate scenarios.

Robust optimization in lung treatment plans accounting for geometric uncertainty.

PubMed

Zhang, Xin; Rong, Yi; Morrill, Steven; Fang, Jian; Narayanasamy, Ganesh; Galhardo, Edvaldo; Maraboyina, Sanjay; Croft, Christopher; Xia, Fen; Penagaricano, Jose

2018-05-01

Robust optimization generates scenario-based plans by a minimax optimization method to find optimal scenario for the trade-off between target coverage robustness and organ-at-risk (OAR) sparing. In this study, 20 lung cancer patients with tumors located at various anatomical regions within the lungs were selected and robust optimization photon treatment plans including intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. The plan robustness was analyzed using perturbed doses with setup error boundary of ±3 mm in anterior/posterior (AP), ±3 mm in left/right (LR), and ±5 mm in inferior/superior (IS) directions from isocenter. Perturbed doses for D 99 , D 98 , and D 95 were computed from six shifted isocenter plans to evaluate plan robustness. Dosimetric study was performed to compare the internal target volume-based robust optimization plans (ITV-IMRT and ITV-VMAT) and conventional PTV margin-based plans (PTV-IMRT and PTV-VMAT). The dosimetric comparison parameters were: ITV target mean dose (D mean ), R 95 (D 95 /D prescription ), Paddick's conformity index (CI), homogeneity index (HI), monitor unit (MU), and OAR doses including lung (D mean , V 20 Gy and V 15 Gy ), chest wall, heart, esophagus, and maximum cord doses. A comparison of optimization results showed the robust optimization plan had better ITV dose coverage, better CI, worse HI, and lower OAR doses than conventional PTV margin-based plans. Plan robustness evaluation showed that the perturbed doses of D 99 , D 98 , and D 95 were all satisfied at least 99% of the ITV to received 95% of prescription doses. It was also observed that PTV margin-based plans had higher MU than robust optimization plans. The results also showed robust optimization can generate plans that offer increased OAR sparing, especially for normal lungs and OARs near or abutting the target. Weak correlation was found between normal lung dose and target size, and no other correlation was observed in this study. © 2018 University of Arkansas for Medical Sciences. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Optimal groundwater security management policies by control of inexact health risks under dual uncertainty in slope factors.

PubMed

Lu, Hongwei; Li, Jing; Ren, Lixia; Chen, Yizhong

2018-05-01

Groundwater remediation is a complicated system with time-consuming and costly challenges, which should be carefully controlled by appropriate groundwater management. This study develops an integrated optimization method for groundwater remediation management regarding cost, contamination distribution and health risk under multiple uncertainties. The integration of health risk into groundwater remediation optimization management is capable of not only adequately considering the influence of health risk on optimal remediation strategies, but also simultaneously completing remediation optimization design and risk assessment. A fuzzy chance-constrained programming approach is presented to handle multiple uncertain properties in the process of health risk assessment. The capabilities and effectiveness of the developed method are illustrated through an application of a naphthalene contaminated case in Anhui, China. Results indicate that (a) the pump-and-treat remediation system leads to a low naphthalene contamination but high remediation cost for a short-time remediation, and natural attenuation significantly affects naphthalene removal from groundwater for a long-time remediation; (b) the weighting coefficients have significant influences on the remediation cost and the performances both for naphthalene concentrations and health risks; (c) an increased level of slope factor (sf) for naphthalene corresponds to more optimal strategies characterized by higher environmental benefits and lower economic sacrifice. The developed method could be simultaneously beneficial for public health and environmental protection. Decision makers could obtain the most appropriate remediation strategies according to their specific requirements with high flexibility of economic, environmental, and risk concerns. Copyright © 2018 Elsevier Ltd. All rights reserved.

Quantitative Decision Making.

ERIC Educational Resources Information Center

Baldwin, Grover H.

The use of quantitative decision making tools provides the decision maker with a range of alternatives among which to decide, permits acceptance and use of the optimal solution, and decreases risk. Training line administrators in the use of these tools can help school business officials obtain reliable information upon which to base district…

Market-based Instruments for optimal control of Invasive Insect Species: B. tabaci in Arizona.

USDA-ARS?s Scientific Manuscript database

Invasive insect species represent a significant economic risk to both the financial viability of agricultural producers and to the sustainability of U.S. agriculture more generally. With the rapid growth of international trade in agricultural commodities of all types, agricultural systems in the U.S...

Using Quantile and Asymmetric Least Squares Regression for Optimal Risk Adjustment.

PubMed

Lorenz, Normann

2017-06-01

In this paper, we analyze optimal risk adjustment for direct risk selection (DRS). Integrating insurers' activities for risk selection into a discrete choice model of individuals' health insurance choice shows that DRS has the structure of a contest. For the contest success function (csf) used in most of the contest literature (the Tullock-csf), optimal transfers for a risk adjustment scheme have to be determined by means of a restricted quantile regression, irrespective of whether insurers are primarily engaged in positive DRS (attracting low risks) or negative DRS (repelling high risks). This is at odds with the common practice of determining transfers by means of a least squares regression. However, this common practice can be rationalized for a new csf, but only if positive and negative DRSs are equally important; if they are not, optimal transfers have to be calculated by means of a restricted asymmetric least squares regression. Using data from German and Swiss health insurers, we find considerable differences between the three types of regressions. Optimal transfers therefore critically depend on which csf represents insurers' incentives for DRS and, if it is not the Tullock-csf, whether insurers are primarily engaged in positive or negative DRS. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Using geostatistics to evaluate cleanup goals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marcon, M.F.; Hopkins, L.P.

1995-12-01

Geostatistical analysis is a powerful predictive tool typically used to define spatial variability in environmental data. The information from a geostatistical analysis using kriging, a geostatistical. tool, can be taken a step further to optimize sampling location and frequency and help quantify sampling uncertainty in both the remedial investigation and remedial design at a hazardous waste site. Geostatistics were used to quantify sampling uncertainty in attainment of a risk-based cleanup goal and determine the optimal sampling frequency necessary to delineate the horizontal extent of impacted soils at a Gulf Coast waste site.

SURE Estimates for a Heteroscedastic Hierarchical Model

PubMed Central

Xie, Xianchao; Kou, S. C.; Brown, Lawrence D.

2014-01-01

Hierarchical models are extensively studied and widely used in statistics and many other scientific areas. They provide an effective tool for combining information from similar resources and achieving partial pooling of inference. Since the seminal work by James and Stein (1961) and Stein (1962), shrinkage estimation has become one major focus for hierarchical models. For the homoscedastic normal model, it is well known that shrinkage estimators, especially the James-Stein estimator, have good risk properties. The heteroscedastic model, though more appropriate for practical applications, is less well studied, and it is unclear what types of shrinkage estimators are superior in terms of the risk. We propose in this paper a class of shrinkage estimators based on Stein’s unbiased estimate of risk (SURE). We study asymptotic properties of various common estimators as the number of means to be estimated grows (p → ∞). We establish the asymptotic optimality property for the SURE estimators. We then extend our construction to create a class of semi-parametric shrinkage estimators and establish corresponding asymptotic optimality results. We emphasize that though the form of our SURE estimators is partially obtained through a normal model at the sampling level, their optimality properties do not heavily depend on such distributional assumptions. We apply the methods to two real data sets and obtain encouraging results. PMID:25301976

Reducing infection risk in implant-based breast-reconstruction surgery: challenges and solutions

PubMed Central

Ooi, Adrian SH; Song, David H

2016-01-01

Implant-based procedures are the most commonly performed method for postmastectomy breast reconstruction. While donor-site morbidity is low, these procedures are associated with a higher risk of reconstructive loss. Many of these are related to infection of the implant, which can lead to prolonged antibiotic treatment, undesired additional surgical procedures, and unsatisfactory results. This review combines a summary of the recent literature regarding implant-related breast-reconstruction infections and combines this with a practical approach to the patient and surgery aimed at reducing this risk. Prevention of infection begins with appropriate reconstructive choice based on an assessment and optimization of risk factors. These include patient and disease characteristics, such as smoking, obesity, large breast size, and immediate reconstructive procedures, as well as adjuvant therapy, such as radiotherapy and chemotherapy. For implant-based breast reconstruction, preoperative planning and organization is key to reducing infection. A logical and consistent intraoperative and postoperative surgical protocol, including appropriate antibiotic choice, mastectomy-pocket creation, implant handling, and considered acellular dermal matrix use contribute toward the reduction of breast-implant infections. PMID:27621667

Risk assessment in the 21st century: roadmap and matrix.

PubMed

Embry, Michelle R; Bachman, Ammie N; Bell, David R; Boobis, Alan R; Cohen, Samuel M; Dellarco, Michael; Dewhurst, Ian C; Doerrer, Nancy G; Hines, Ronald N; Moretto, Angelo; Pastoor, Timothy P; Phillips, Richard D; Rowlands, J Craig; Tanir, Jennifer Y; Wolf, Douglas C; Doe, John E

2014-08-01

Abstract The RISK21 integrated evaluation strategy is a problem formulation-based exposure-driven risk assessment roadmap that takes advantage of existing information to graphically represent the intersection of exposure and toxicity data on a highly visual matrix. This paper describes in detail the process for using the roadmap and matrix. The purpose of this methodology is to optimize the use of prior information and testing resources (animals, time, facilities, and personnel) to efficiently and transparently reach a risk and/or safety determination. Based on the particular problem, exposure and toxicity data should have sufficient precision to make such a decision. Estimates of exposure and toxicity, bounded by variability and/or uncertainty, are plotted on the X- and Y-axes of the RISK21 matrix, respectively. The resulting intersection is a highly visual representation of estimated risk. Decisions can then be made to increase precision in the exposure or toxicity estimates or declare that the available information is sufficient. RISK21 represents a step forward in the goal to introduce new methodologies into 21st century risk assessment. Indeed, because of its transparent and visual process, RISK21 has the potential to widen the scope of risk communication beyond those with technical expertise.

Deriving an optimal threshold of waist circumference for detecting cardiometabolic risk in sub-Saharan Africa.

PubMed

Ekoru, K; Murphy, G A V; Young, E H; Delisle, H; Jerome, C S; Assah, F; Longo-Mbenza, B; Nzambi, J P D; On'Kin, J B K; Buntix, F; Muyer, M C; Christensen, D L; Wesseh, C S; Sabir, A; Okafor, C; Gezawa, I D; Puepet, F; Enang, O; Raimi, T; Ohwovoriole, E; Oladapo, O O; Bovet, P; Mollentze, W; Unwin, N; Gray, W K; Walker, R; Agoudavi, K; Siziya, S; Chifamba, J; Njelekela, M; Fourie, C M; Kruger, S; Schutte, A E; Walsh, C; Gareta, D; Kamali, A; Seeley, J; Norris, S A; Crowther, N J; Pillay, D; Kaleebu, P; Motala, A A; Sandhu, M S

2017-10-03

Waist circumference (WC) thresholds derived from western populations continue to be used in sub-Saharan Africa (SSA) despite increasing evidence of ethnic variation in the association between adiposity and cardiometabolic disease and availability of data from African populations. We aimed to derive a SSA-specific optimal WC cut-point for identifying individuals at increased cardiometabolic risk. We used individual level cross-sectional data on 24 181 participants aged ⩾15 years from 17 studies conducted between 1990 and 2014 in eight countries in SSA. Receiver operating characteristic curves were used to derive optimal WC cut-points for detecting the presence of at least two components of metabolic syndrome (MS), excluding WC. The optimal WC cut-point was 81.2 cm (95% CI 78.5-83.8 cm) and 81.0 cm (95% CI 79.2-82.8 cm) for men and women, respectively, with comparable accuracy in men and women. Sensitivity was higher in women (64%, 95% CI 63-65) than in men (53%, 95% CI 51-55), and increased with the prevalence of obesity. Having WC above the derived cut-point was associated with a twofold probability of having at least two components of MS (age-adjusted odds ratio 2.6, 95% CI 2.4-2.9, for men and 2.2, 95% CI 2.0-2.3, for women). The optimal WC cut-point for identifying men at increased cardiometabolic risk is lower (⩾81.2 cm) than current guidelines (⩾94.0 cm) recommend, and similar to that in women in SSA. Prospective studies are needed to confirm these cut-points based on cardiometabolic outcomes.International Journal of Obesity advance online publication, 31 October 2017; doi:10.1038/ijo.2017.240.

Fatalism, optimism, spirituality, depressive symptoms and stroke outcome: A population-based analysis

PubMed Central

Morgenstern, Lewis B.; Sánchez, Brisa N.; Skolarus, Lesli E.; Garcia, Nelda; Risser, Jan M.H.; Wing, Jeffrey J.; Smith, Melinda A.; Zahuranec, Darin B.; Lisabeth, Lynda D.

2011-01-01

Background and Purpose We sought to describe the association of spirituality, optimism, fatalism and depressive symptoms with initial stroke severity, stroke recurrence and post-stroke mortality. Methods Stroke cases June 2004–December 2008 were ascertained in Nueces County, Texas. Patients without aphasia were queried on their recall of depressive symptoms, fatalism, optimism, and non-organizational spirituality before stroke using validated scales. The association between scales and stroke outcomes was studied using multiple linear regression with log-transformed NIHSS and Cox proportional hazards regression for recurrence and mortality. Results 669 patients participated, 48.7% were women. In fully adjusted models, an increase in fatalism from the first to third quartile was associated with all-cause mortality (HR=1.41, 95%CI: 1.06, 1.88), marginally associated with risk of recurrence (HR=1.35, 95%CI: 0.97, 1.88), but not stroke severity. Similarly, an increase in depressive symptoms was associated with increased mortality (HR=1.32, 95%CI: 1.02, 1.72), marginally associated with stroke recurrence (HR=1.22, CI: 0.93, 1.62), and with a 9.0% increase in stroke severity (95%CI: 0.01, 18.0). Depressive symptoms altered the fatalism-mortality association such that the association of fatalism and mortality was more pronounced for patients reporting no depressive symptoms. Neither spirituality nor optimism conferred a significant effect on stroke severity, recurrence or mortality. Conclusions Among patients who have already had a stroke, self-described pre-stroke depressive symptoms and fatalism, but not optimism or spirituality, are associated with increased risk of stroke recurrence and mortality. Unconventional risk factors may explain some of the variability in stroke outcomes observed in populations, and may be novel targets for intervention. PMID:21940963

Active and Reactive Power Optimal Dispatch Associated with Load and DG Uncertainties in Active Distribution Network

NASA Astrophysics Data System (ADS)

Gao, F.; Song, X. H.; Zhang, Y.; Li, J. F.; Zhao, S. S.; Ma, W. Q.; Jia, Z. Y.

2017-05-01

In order to reduce the adverse effects of uncertainty on optimal dispatch in active distribution network, an optimal dispatch model based on chance-constrained programming is proposed in this paper. In this model, the active and reactive power of DG can be dispatched at the aim of reducing the operating cost. The effect of operation strategy on the cost can be reflected in the objective which contains the cost of network loss, DG curtailment, DG reactive power ancillary service, and power quality compensation. At the same time, the probabilistic constraints can reflect the operation risk degree. Then the optimal dispatch model is simplified as a series of single stage model which can avoid large variable dimension and improve the convergence speed. And the single stage model is solved using a combination of particle swarm optimization (PSO) and point estimate method (PEM). Finally, the proposed optimal dispatch model and method is verified by the IEEE33 test system.

Anthropometric cutoff values for predicting metabolic syndrome in a Saudi community: from the SAUDI-DM study.

PubMed

Al-Rubean, Khalid; Youssef, Amira M; AlFarsi, Yousuf; Al-Sharqawi, Ahmad H; Bawazeer, Nahla; AlOtaibi, Mohammad T; AlRumaih, Fahd Issa; Zaidi, Muhammad Shoaib

2017-01-01

The prevalence of metabolic syndrome varies widely by ethnicity and by the criteria used in its definition. To identify the optimal cutoff values for waist circumference (WC), waist-to-hip ratio (WHR) and body mass index (BMI) for identifying metabolic syndrome among the Saudi population. Nationwide household cross-sectional population-based survey. Thirteen health sectors in Saudi Arabia. We used data for subjects in the Saudi Abnormal Glucose Metabolism and Diabetes Impact Study (SAUDI-DM), which was conducted from 2007 to 2009. Using International Diabetes Federation (IDF) criteria, metabolic syndrome and its different components were assessed using anthropometric measurements, blood pressure, fasting plasma glucose, triglycerides and HDL cholesterol. Receiver operating characteristic (ROC) curves were generated to assess sensitivity and specificity for different cutoff values of WC, WHR, and BMI. The Youden index was used to calculate the optimal cutoff value for each anthropometric measurement. Optimal cutoff value for WC, WHR, and BMI for identifying the risk of metabolic syndrome. The prevalence of two or more risk factors for metabolic syndrome was observed in 43.42% of the total cohort of 12126 study participants >=18 years of age. The presence of two or more risk factors were significantly higher among men (46.81%) than women (40.53%) (P < .001). The optimal cutoff values for WC, WHR, and BMI were 92 cm, 0.89, and 25 kg/m2 for men and 87 cm, 0.81 and 28 kg/m2 for women for identifying the risk of metabolic syndrome. The prevalence of elevated triglycerides, blood pressure, and fasting plasma glucose significantly increased with age for both genders. The proposed WC cutoff values were better than WHR and BMI in predicting metabolic syndrome and could be used for screening people at high risk for metabolic syndrome in the Saudi population. No direct measure of body fatness and fat distribution, cross-sectional design.

Approach to proliferation risk assessment based on multiple objective analysis framework

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrianov, A.; Kuptsov, I.; Studgorodok 1, Obninsk, Kaluga region, 249030

2013-07-01

The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materialsmore » circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.« less

Mental health of a police force: estimating prevalence of work-related depression in Australia without a direct national measure.

PubMed

Lawson, Katrina J; Rodwell, John J; Noblet, Andrew J

2012-06-01

The risk of work-related depression in Australia was estimated based on a survey of 631 police officers. Psychological wellbeing and psychological distress items were mapped onto a measure of depression to identify optimal cutoff points. Based on a sample of police officers, Australian workers, in general, are at risk of depression when general psychological wellbeing is considerably compromised. Large-scale estimation of work-related depression in the broader population of employed persons in Australia is reasonable. The relatively high prevalence of depression among police officers emphasizes the need to examine prevalence rates of depression among Australian employees.

Dynamic trajectory-based couch motion for improvement of radiation therapy trajectories in cranial SRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, R. Lee; Thomas, Christopher G., E-mail: Chris.Thomas@cdha.nshealth.ca; Department of Medical Physics, Nova Scotia Cancer Centre, Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia B3H 1V7

2015-05-15

Purpose: To investigate potential improvement in external beam stereotactic radiation therapy plan quality for cranial cases using an optimized dynamic gantry and patient support couch motion trajectory, which could minimize exposure to sensitive healthy tissue. Methods: Anonymized patient anatomy and treatment plans of cranial cancer patients were used to quantify the geometric overlap between planning target volumes and organs-at-risk (OARs) based on their two-dimensional projection from source to a plane at isocenter as a function of gantry and couch angle. Published dose constraints were then used as weighting factors for the OARs to generate a map of couch-gantry coordinate space,more » indicating degree of overlap at each point in space. A couch-gantry collision space was generated by direct measurement on a linear accelerator and couch using an anthropomorphic solid-water phantom. A dynamic, fully customizable algorithm was written to generate a navigable ideal trajectory for the patient specific couch-gantry space. The advanced algorithm can be used to balance the implementation of absolute minimum values of overlap with the clinical practicality of large-scale couch motion and delivery time. Optimized cranial cancer treatment trajectories were compared to conventional treatment trajectories. Results: Comparison of optimized treatment trajectories with conventional treatment trajectories indicated an average decrease in mean dose to the OARs of 19% and an average decrease in maximum dose to the OARs of 12%. Degradation was seen for homogeneity index (6.14% ± 0.67%–5.48% ± 0.76%) and conformation number (0.82 ± 0.02–0.79 ± 0.02), but neither was statistically significant. Removal of OAR constraints from volumetric modulated arc therapy optimization reveals that reduction in dose to OARs is almost exclusively due to the optimized trajectory and not the OAR constraints. Conclusions: The authors’ study indicated that simultaneous couch and gantry motion during radiation therapy to minimize the geometrical overlap in the beams-eye-view of target volumes and the organs-at-risk can have an appreciable dose reduction to organs-at-risk.« less

Deconstructing Pretest Risk Enrichment to Optimize Prediction of Psychosis in Individuals at Clinical High Risk.

PubMed

Fusar-Poli, Paolo; Rutigliano, Grazia; Stahl, Daniel; Schmidt, André; Ramella-Cravaro, Valentina; Hitesh, Shetty; McGuire, Philip

2016-12-01

Pretest risk estimation is routinely used in clinical medicine to inform further diagnostic testing in individuals with suspected diseases. To our knowledge, the overall characteristics and specific determinants of pretest risk of psychosis onset in individuals undergoing clinical high risk (CHR) assessment are unknown. To investigate the characteristics and determinants of pretest risk of psychosis onset in individuals undergoing CHR assessment and to develop and externally validate a pretest risk stratification model. Clinical register-based cohort study. Individuals were drawn from electronic, real-world, real-time clinical records relating to routine mental health care of CHR services in South London and the Maudsley National Health Service Trust in London, United Kingdom. The study included nonpsychotic individuals referred on suspicion of psychosis risk and assessed by the Outreach and Support in South London CHR service from 2002 to 2015. Model development and validation was performed with machine-learning methods based on Least Absolute Shrinkage and Selection Operator for Cox proportional hazards model. Pretest risk of psychosis onset in individuals undergoing CHR assessment. Predictors included age, sex, age × sex interaction, race/ethnicity, socioeconomic status, marital status, referral source, and referral year. A total of 710 nonpsychotic individuals undergoing CHR assessment were included. The mean age was 23 years. Three hundred ninety-nine individuals were men (56%), their race/ethnicity was heterogenous, and they were referred from a variety of sources. The cumulative 6-year pretest risk of psychosis was 14.55% (95% CI, 11.71% to 17.99%), confirming substantial pretest risk enrichment during the recruitment of individuals undergoing CHR assessment. Race/ethnicity and source of referral were associated with pretest risk enrichment. The predictive model based on these factors was externally validated, showing moderately good discrimination and sufficient calibration. It was used to stratify individuals undergoing CHR assessment into 4 classes of pretest risk (6-year): low, 3.39% (95% CI, 0.96% to 11.56%); moderately low, 11.58% (95% CI, 8.10% to 16.40%); moderately high, 23.69% (95% CI, 16.58% to 33.20%); and high, 53.65% (95% CI, 36.78% to 72.46%). Significant risk enrichment occurs before individuals are assessed for a suspected CHR state. Race/ethnicity and source of referral are associated with pretest risk enrichment in individuals undergoing CHR assessment. A stratification model can identify individuals at differential pretest risk of psychosis. Identification of these subgroups may inform outreach campaigns and subsequent testing and eventually optimize psychosis prediction.

Preoperative Screening.

PubMed

Marwell, Julianna G; Heflin, Mitchell T; McDonald, Shelley R

2018-02-01

Older adults undergoing elective surgical procedures suffer higher rates of morbidity and mortality than younger patients. A geriatric-focused preoperative evaluation can identify risk factors for complications and opportunities for health optimization and care coordination. Key components of a geriatric preoperative evaluation include (1) assessments of function, mobility, cognition, and mental health; (2) reviews of medical conditions and medications; and (3) discussion of risks, preferences, and goals of care. A geriatric-focused, team-based approach can improve surgical outcomes and patient experience. Published by Elsevier Inc.

Gradient descent for robust kernel-based regression

NASA Astrophysics Data System (ADS)

Guo, Zheng-Chu; Hu, Ting; Shi, Lei

2018-06-01

In this paper, we study the gradient descent algorithm generated by a robust loss function over a reproducing kernel Hilbert space (RKHS). The loss function is defined by a windowing function G and a scale parameter σ, which can include a wide range of commonly used robust losses for regression. There is still a gap between theoretical analysis and optimization process of empirical risk minimization based on loss: the estimator needs to be global optimal in the theoretical analysis while the optimization method can not ensure the global optimality of its solutions. In this paper, we aim to fill this gap by developing a novel theoretical analysis on the performance of estimators generated by the gradient descent algorithm. We demonstrate that with an appropriately chosen scale parameter σ, the gradient update with early stopping rules can approximate the regression function. Our elegant error analysis can lead to convergence in the standard L 2 norm and the strong RKHS norm, both of which are optimal in the mini-max sense. We show that the scale parameter σ plays an important role in providing robustness as well as fast convergence. The numerical experiments implemented on synthetic examples and real data set also support our theoretical results.

Understanding Engagement in HIV Risk and Prevention Research Among Black Young Men Who Have Sex with Men and Transgender Women in the District of Columbia.

PubMed

Glick, Sara Nelson; Houston, Ebony; Peterson, James; Kuo, Irene; Magnus, Manya

2016-08-01

To develop optimal methods to study sexual health among black young men who have sex with men and transgender women (BYMSM/TW). We conducted a mixed-methods prospective study to identify recruitment and retention strategies for BYMSM/TW (age 16-21) in Washington D.C., and describe HIV risk behaviors and context. Incentivized peer referral was highly productive, and 60% of BYMSM/TW were retained for 3 months. Participants reported high levels of sexual risk, homophobia, racism, and maternal support. BYMSM/TW studies should utilize a combination of peer-based, in-person, and technology-based recruiting strategies. Additional research is needed to leverage mobile technology and social media to enhance retention.

An emerging evidence base for the management of neonatal hypoglycaemia.

PubMed

Harding, Jane E; Harris, Deborah L; Hegarty, Joanne E; Alsweiler, Jane M; McKinlay, Christopher Jd

2017-01-01

Neonatal hypoglycaemia is common, and screening and treatment of babies considered at risk is widespread, despite there being little reliable evidence upon which to base management decisions. Although there is now evidence about which babies are at greatest risk, the threshold for diagnosis, best approach to treatment and later outcomes all remain uncertain. Recent studies suggest that treatment with dextrose gel is safe and effective and may help support breast feeding. Thresholds for intervention require a wide margin of safety in light of information that babies with glycaemic instability and with low glucose concentrations may be associated with a higher risk of later higher order cognitive and learning problems. Randomised trials are urgently needed to inform optimal thresholds for intervention and appropriate treatment strategies. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

An Emerging Evidence Base for the Management of Neonatal Hypoglycaemia

PubMed Central

Harding, Jane E; Harris, Deborah L; Hegarty, Joanne E; Alsweiler, Jane M; McKinlay, Christopher JD

2016-01-01

Neonatal hypoglycaemia is common, and screening and treatment of babies considered at risk is widespread, despite there being little reliable evidence upon which to base management decisions. Although there is now evidence about which babies are at greatest risk, the threshold for diagnosis, best approach to treatment and later outcomes all remain uncertain. Recent studies suggest that treatment with dextrose gel is safe and effective and may help support breast feeding. Thresholds for intervention require a wide margin of safety in light of information that babies with glycaemic instability and with low glucose concentrations may be associated with a higher risk of later higher order cognitive and learning problems. Randomised trials are urgently needed to inform optimal thresholds for intervention and appropriate treatment strategies. PMID:27989586

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt Derr; Milos Manic

Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculationmore » DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.« less

A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

NASA Astrophysics Data System (ADS)

Liu, P.

2013-12-01

Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

Optimization and determination of polycyclic aromatic hydrocarbons in biochar-based fertilizers.

PubMed

Chen, Ping; Zhou, Hui; Gan, Jay; Sun, Mingxing; Shang, Guofeng; Liu, Liang; Shen, Guoqing

2015-03-01

The agronomic benefit of biochar has attracted widespread attention to biochar-based fertilizers. However, the inevitable presence of polycyclic aromatic hydrocarbons in biochar is a matter of concern because of the health and ecological risks of these compounds. The strong adsorption of polycyclic aromatic hydrocarbons to biochar complicates their analysis and extraction from biochar-based fertilizers. In this study, we optimized and validated a method for determining the 16 priority polycyclic aromatic hydrocarbons in biochar-based fertilizers. Results showed that accelerated solvent extraction exhibited high extraction efficiency. Based on a Box-Behnken design with a triplicate central point, accelerated solvent extraction was used under the following optimal operational conditions: extraction temperature of 78°C, extraction time of 17 min, and two static cycles. The optimized method was validated by assessing the linearity of analysis, limit of detection, limit of quantification, recovery, and application to real samples. The results showed that the 16 polycyclic aromatic hydrocarbons exhibited good linearity, with a correlation coefficient of 0.996. The limits of detection varied between 0.001 (phenanthrene) and 0.021 mg/g (benzo[ghi]perylene), and the limits of quantification varied between 0.004 (phenanthrene) and 0.069 mg/g (benzo[ghi]perylene). The relative recoveries of the 16 polycyclic aromatic hydrocarbons were 70.26-102.99%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Replica Approach for Minimal Investment Risk with Cost

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2018-06-01

In the present work, the optimal portfolio minimizing the investment risk with cost is discussed analytically, where an objective function is constructed in terms of two negative aspects of investment, the risk and cost. We note the mathematical similarity between the Hamiltonian in the mean-variance model and the Hamiltonians in the Hopfield model and the Sherrington-Kirkpatrick model, show that we can analyze this portfolio optimization problem by using replica analysis, and derive the minimal investment risk with cost and the investment concentration of the optimal portfolio. Furthermore, we validate our proposed method through numerical simulations.

Risk-aware multi-armed bandit problem with application to portfolio selection

PubMed Central

Huo, Xiaoguang

2017-01-01

Sequential portfolio selection has attracted increasing interest in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem addresses the primary difficulty in sequential decision-making under uncertainty, namely the exploration versus exploitation dilemma, and therefore provides a natural connection to portfolio selection. In this paper, we incorporate risk awareness into the classic multi-armed bandit setting and introduce an algorithm to construct portfolio. Through filtering assets based on the topological structure of the financial market and combining the optimal multi-armed bandit policy with the minimization of a coherent risk measure, we achieve a balance between risk and return. PMID:29291122

Risk-aware multi-armed bandit problem with application to portfolio selection.

PubMed

Huo, Xiaoguang; Fu, Feng

2017-11-01

Sequential portfolio selection has attracted increasing interest in the machine learning and quantitative finance communities in recent years. As a mathematical framework for reinforcement learning policies, the stochastic multi-armed bandit problem addresses the primary difficulty in sequential decision-making under uncertainty, namely the exploration versus exploitation dilemma, and therefore provides a natural connection to portfolio selection. In this paper, we incorporate risk awareness into the classic multi-armed bandit setting and introduce an algorithm to construct portfolio. Through filtering assets based on the topological structure of the financial market and combining the optimal multi-armed bandit policy with the minimization of a coherent risk measure, we achieve a balance between risk and return.

Dose-mass inverse optimization for minimally moving thoracic lesions

NASA Astrophysics Data System (ADS)

Mihaylov, I. B.; Moros, E. G.

2015-05-01

In the past decade, several different radiotherapy treatment plan evaluation and optimization schemes have been proposed as viable approaches, aiming for dose escalation or an increase of healthy tissue sparing. In particular, it has been argued that dose-mass plan evaluation and treatment plan optimization might be viable alternatives to the standard of care, which is realized through dose-volume evaluation and optimization. The purpose of this investigation is to apply dose-mass optimization to a cohort of lung cancer patients and compare the achievable healthy tissue sparing to that one achievable through dose-volume optimization. Fourteen non-small cell lung cancer (NSCLC) patient plans were studied retrospectively. The range of tumor motion was less than 0.5 cm and motion management in the treatment planning process was not considered. For each case, dose-volume (DV)-based and dose-mass (DM)-based optimization was performed. Nine-field step-and-shoot IMRT was used, with all of the optimization parameters kept the same between DV and DM optimizations. Commonly used dosimetric indices (DIs) such as dose to 1% the spinal cord volume, dose to 50% of the esophageal volume, and doses to 20 and 30% of healthy lung volumes were used for cross-comparison. Similarly, mass-based indices (MIs), such as doses to 20 and 30% of healthy lung masses, 1% of spinal cord mass, and 33% of heart mass, were also tallied. Statistical equivalence tests were performed to quantify the findings for the entire patient cohort. Both DV and DM plans for each case were normalized such that 95% of the planning target volume received the prescribed dose. DM optimization resulted in more organs at risk (OAR) sparing than DV optimization. The average sparing of cord, heart, and esophagus was 23, 4, and 6%, respectively. For the majority of the DIs, DM optimization resulted in lower lung doses. On average, the doses to 20 and 30% of healthy lung were lower by approximately 3 and 4%, whereas lung volumes receiving 2000 and 3000 cGy were lower by 3 and 2%, respectively. The behavior of MIs was very similar. The statistical analyses of the results again indicated better healthy anatomical structure sparing with DM optimization. The presented findings indicate that dose-mass-based optimization results in statistically significant OAR sparing as compared to dose-volume-based optimization for NSCLC. However, the sparing is case-dependent and it is not observed for all tallied dosimetric endpoints.

Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy

NASA Astrophysics Data System (ADS)

Ajdari, Ali; Ghate, Archis; Kim, Minsun

2018-04-01

Recent theoretical research on spatiobiologically integrated radiotherapy has focused on optimization models that adapt fluence-maps to the evolution of tumor state, for example, cell densities, as observed in quantitative functional images acquired over the treatment course. We propose an optimization model that adapts the length of the treatment course as well as the fluence-maps to such imaged tumor state. Specifically, after observing the tumor cell densities at the beginning of a session, the treatment planner solves a group of convex optimization problems to determine an optimal number of remaining treatment sessions, and a corresponding optimal fluence-map for each of these sessions. The objective is to minimize the total number of tumor cells remaining (TNTCR) at the end of this proposed treatment course, subject to upper limits on the biologically effective dose delivered to the organs-at-risk. This fluence-map is administered in future sessions until the next image is available, and then the number of sessions and the fluence-map are re-optimized based on the latest cell density information. We demonstrate via computer simulations on five head-and-neck test cases that such adaptive treatment-length and fluence-map planning reduces the TNTCR and increases the biological effect on the tumor while employing shorter treatment courses, as compared to only adapting fluence-maps and using a pre-determined treatment course length based on one-size-fits-all guidelines.

Development of a risk assessment tool for projecting individualized probabilities of developing breast cancer for Chinese women.

PubMed

Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang

2014-11-01

The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation.

Evaluation of Spacecraft Shielding Effectiveness for Radiation Protection

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Wilson, John W.

1999-01-01

The potential for serious health risks from solar particle events (SPE) and galactic cosmic rays (GCR) is a critical issue in the NASA strategic plan for the Human Exploration and Development of Space (HEDS). The excess cost to protect against the GCR and SPE due to current uncertainties in radiation transmission properties and cancer biology could be exceedingly large based on the excess launch costs to shield against uncertainties. The development of advanced shielding concepts is an important risk mitigation area with the potential to significantly reduce risk below conventional mission designs. A key issue in spacecraft material selection is the understanding of nuclear reactions on the transmission properties of materials. High-energy nuclear particles undergo nuclear reactions in passing through materials and tissue altering their composition and producing new radiation types. Spacecraft and planetary habitat designers can utilize radiation transport codes to identify optimal materials for lowering exposures and to optimize spacecraft design to reduce astronaut exposures. To reach these objectives will require providing design engineers with accurate data bases and computationally efficient software for describing the transmission properties of space radiation in materials. Our program will reduce the uncertainty in the transmission properties of space radiation by improving the theoretical description of nuclear reactions and radiation transport, and provide accurate physical descriptions of the track structure of microscopic energy deposition.

Risk Analysis for Resource Planning Optimization

NASA Technical Reports Server (NTRS)

Chueng, Kar-Ming

2008-01-01

The main purpose of this paper is to introduce a risk management approach that allows planners to quantify the risk and efficiency tradeoff in the presence of uncertainties, and to make forward-looking choices in the development and execution of the plan. Demonstrate a planning and risk analysis framework that tightly integrates mathematical optimization, empirical simulation, and theoretical analysis techniques to solve complex problems.

The Integrated Medical Model

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles; Saile, Lynn; Freiere deCarvalho, Mary; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2010-01-01

The goals of the Integrated Medical Model (IMM) are to develop an integrated, quantified, evidence-based decision support tool useful to crew health and mission planners and to help align science, technology, and operational activities intended to optimize crew health, safety, and mission success. Presentation slides address scope and approach, beneficiaries of IMM capabilities, history, risk components, conceptual models, development steps, and the evidence base. Space adaptation syndrome is used to demonstrate the model's capabilities.

Risk-based management of invading plant disease.

PubMed

Hyatt-Twynam, Samuel R; Parnell, Stephen; Stutt, Richard O J H; Gottwald, Tim R; Gilligan, Christopher A; Cunniffe, Nik J

2017-05-01

Effective control of plant disease remains a key challenge. Eradication attempts often involve removal of host plants within a certain radius of detection, targeting asymptomatic infection. Here we develop and test potentially more effective, epidemiologically motivated, control strategies, using a mathematical model previously fitted to the spread of citrus canker in Florida. We test risk-based control, which preferentially removes hosts expected to cause a high number of infections in the remaining host population. Removals then depend on past patterns of pathogen spread and host removal, which might be nontransparent to affected stakeholders. This motivates a variable radius strategy, which approximates risk-based control via removal radii that vary by location, but which are fixed in advance of any epidemic. Risk-based control outperforms variable radius control, which in turn outperforms constant radius removal. This result is robust to changes in disease spread parameters and initial patterns of susceptible host plants. However, efficiency degrades if epidemiological parameters are incorrectly characterised. Risk-based control including additional epidemiology can be used to improve disease management, but it requires good prior knowledge for optimal performance. This focuses attention on gaining maximal information from past epidemics, on understanding model transferability between locations and on adaptive management strategies that change over time. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Modeling and managing risk early in software development

NASA Technical Reports Server (NTRS)

Briand, Lionel C.; Thomas, William M.; Hetmanski, Christopher J.

1993-01-01

In order to improve the quality of the software development process, we need to be able to build empirical multivariate models based on data collectable early in the software process. These models need to be both useful for prediction and easy to interpret, so that remedial actions may be taken in order to control and optimize the development process. We present an automated modeling technique which can be used as an alternative to regression techniques. We show how it can be used to facilitate the identification and aid the interpretation of the significant trends which characterize 'high risk' components in several Ada systems. Finally, we evaluate the effectiveness of our technique based on a comparison with logistic regression based models.

Narcissistic personality and risk perception among Chinese aviators: The mediating role of promotion focus.

PubMed

Ju, Chengting; Ji, Ming; Lan, Jijun; You, Xuqun

2017-12-01

Optimism bias is a crucial feature of risk perception that leads to increased risk-taking behaviour, which is a particularly salient issue among pilots in aviation settings due to the high-stakes nature of flight. The current study sought to address the roles of narcissism and promotion focus on optimism bias in risk perception in aviation context. Participants were 239 male flight cadets from the Civil Aviation Flight University of China who completed the Narcissistic Personality Inventory-13, the Work Regulatory Focus Scale, and an indirect measure of unrealistic optimism in risk perception, which measured risk perception for the individual and the risk assumed by other individuals performing the same task. Higher narcissism increased the likelihood of underestimating personal risks, an effect that was mediated by high promotion focus motivation, such that high narcissism led to high promotion focus motivation. The findings have important implications for improving the accuracy of risk perception in aviation risks among aviators. © 2016 International Union of Psychological Science.

EUD-based biological optimization for carbon ion therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brüningk, Sarah C., E-mail: sarah.brueningk@icr.ac.uk; Kamp, Florian; Wilkens, Jan J.

2015-11-15

Purpose: Treatment planning for carbon ion therapy requires an accurate modeling of the biological response of each tissue to estimate the clinical outcome of a treatment. The relative biological effectiveness (RBE) accounts for this biological response on a cellular level but does not refer to the actual impact on the organ as a whole. For photon therapy, the concept of equivalent uniform dose (EUD) represents a simple model to take the organ response into account, yet so far no formulation of EUD has been reported that is suitable to carbon ion therapy. The authors introduce the concept of an equivalentmore » uniform effect (EUE) that is directly applicable to both ion and photon therapies and exemplarily implemented it as a basis for biological treatment plan optimization for carbon ion therapy. Methods: In addition to a classical EUD concept, which calculates a generalized mean over the RBE-weighted dose distribution, the authors propose the EUE to simplify the optimization process of carbon ion therapy plans. The EUE is defined as the biologically equivalent uniform effect that yields the same probability of injury as the inhomogeneous effect distribution in an organ. Its mathematical formulation is based on the generalized mean effect using an effect-volume parameter to account for different organ architectures and is thus independent of a reference radiation. For both EUD concepts, quadratic and logistic objective functions are implemented into a research treatment planning system. A flexible implementation allows choosing for each structure between biological effect constraints per voxel and EUD constraints per structure. Exemplary treatment plans are calculated for a head-and-neck patient for multiple combinations of objective functions and optimization parameters. Results: Treatment plans optimized using an EUE-based objective function were comparable to those optimized with an RBE-weighted EUD-based approach. In agreement with previous results from photon therapy, the optimization by biological objective functions resulted in slightly superior treatment plans in terms of final EUD for the organs at risk (OARs) compared to voxel-based optimization approaches. This observation was made independent of the underlying objective function metric. An absolute gain in OAR sparing was observed for quadratic objective functions, whereas intersecting DVHs were found for logistic approaches. Even for considerable under- or overestimations of the used effect- or dose–volume parameters during the optimization, treatment plans were obtained that were of similar quality as the results of a voxel-based optimization. Conclusions: EUD-based optimization with either of the presented concepts can successfully be applied to treatment plan optimization. This makes EUE-based optimization for carbon ion therapy a useful tool to optimize more specifically in the sense of biological outcome while voxel-to-voxel variations of the biological effectiveness are still properly accounted for. This may be advantageous in terms of computational cost during treatment plan optimization but also enables a straight forward comparison of different fractionation schemes or treatment modalities.« less

Two-Step Approach for the Prediction of Future Type 2 Diabetes Risk

PubMed Central

Abdul-Ghani, Muhammad A.; Abdul-Ghani, Tamam; Stern, Michael P.; Karavic, Jasmina; Tuomi, Tiinamaija; Bo, Insoma; DeFronzo, Ralph A.; Groop, Leif

2011-01-01

OBJECTIVE To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis of a multivariate logistic model and 1-h plasma glucose concentration (1-h PG). RESEARCH DESIGN AND METHODS The model was developed in a cohort of 1,562 nondiabetic subjects from the San Antonio Heart Study (SAHS) and validated in 2,395 nondiabetic subjects in the Botnia Study. A risk score on the basis of anthropometric parameters, plasma glucose and lipid profile, and blood pressure was computed for each subject. Subjects with a risk score above a certain cut point were considered to represent high-risk individuals, and their 1-h PG concentration during the oral glucose tolerance test was used to further refine their future T2DM risk. RESULTS We used the San Antonio Diabetes Prediction Model (SADPM) to generate the initial risk score. A risk-score value of 0.065 was found to be an optimal cut point for initial screening and selection of high-risk individuals. A 1-h PG concentration >140 mg/dL in high-risk individuals (whose risk score was >0.065) was the optimal cut point for identification of subjects at increased risk. The two cut points had 77.8, 77.4, and 44.8% (for the SAHS) and 75.8, 71.6, and 11.9% (for the Botnia Study) sensitivity, specificity, and positive predictive value, respectively, in the SAHS and Botnia Study. CONCLUSIONS A two-step model, based on the combination of the SADPM and 1-h PG, is a useful tool for the identification of high-risk Mexican-American and Caucasian individuals. PMID:21788628

Risk Factors for Malnutrition Among Children With Cerebral Palsy in Botswana.

PubMed

Johnson, Allison; Gambrah-Sampaney, Claudia; Khurana, Esha; Baier, James; Baranov, Esther; Monokwane, Baphaleng; Bearden, David R

2017-05-01

Children with cerebral palsy in low-resource settings are at high risk of malnutrition, which further increases their risk of poor health outcomes. However, there are few available data on specific risk factors for malnutrition among children with cerebral palsy in the developing world. We performed a case-control study among children with cerebral palsy receiving care at a tertiary care hospital in Gaborone, Botswana. Children with cerebral palsy and malnutrition were identified according to World Health Organization growth curves and compared with subjects with cerebral palsy without malnutrition. Risk factors for malnutrition were identified using multivariable logistic regression models. These risk factors were then used to generate a Malnutrition Risk Score, and Receiver Operating Characteristic curves were used to identify optimal cutoffs to identify subjects at high risk of malnutrition. We identified 61 children with cerebral palsy, 26 of whom (43%) met criteria for malnutrition. Nonambulatory status (odds ratio 13.8, 95% confidence interval [CI] 3.8-50.1, P < 0.001) and a composite measure of socioeconomic status (odds ratio 1.6, 95% CI 1.0-2.5, P = 0.03) were the strongest risk factors for malnutrition. A Malnutrition Risk Score was constructed based on these risk factors, and receiver operating characteristic curve analysis demonstrated excellent performance characteristics of this score (area under the curve 0.92, 95% CI 0.89-0.94). Malnutrition is common among children with cerebral palsy in Botswana, and a simple risk score may help identify children with the highest risk. Further studies are needed to validate this screening tool and to determine optimal nutritional interventions in this population. Copyright © 2017 Elsevier Inc. All rights reserved.

Applying Risk Prediction Models to Optimize Lung Cancer Screening: Current Knowledge, Challenges, and Future Directions.

PubMed

Sakoda, Lori C; Henderson, Louise M; Caverly, Tanner J; Wernli, Karen J; Katki, Hormuzd A

2017-12-01

Risk prediction models may be useful for facilitating effective and high-quality decision-making at critical steps in the lung cancer screening process. This review provides a current overview of published lung cancer risk prediction models and their applications to lung cancer screening and highlights both challenges and strategies for improving their predictive performance and use in clinical practice. Since the 2011 publication of the National Lung Screening Trial results, numerous prediction models have been proposed to estimate the probability of developing or dying from lung cancer or the probability that a pulmonary nodule is malignant. Respective models appear to exhibit high discriminatory accuracy in identifying individuals at highest risk of lung cancer or differentiating malignant from benign pulmonary nodules. However, validation and critical comparison of the performance of these models in independent populations are limited. Little is also known about the extent to which risk prediction models are being applied in clinical practice and influencing decision-making processes and outcomes related to lung cancer screening. Current evidence is insufficient to determine which lung cancer risk prediction models are most clinically useful and how to best implement their use to optimize screening effectiveness and quality. To address these knowledge gaps, future research should be directed toward validating and enhancing existing risk prediction models for lung cancer and evaluating the application of model-based risk calculators and its corresponding impact on screening processes and outcomes.

Optimizing Cardiovascular Benefits of Exercise: A Review of Rodent Models

PubMed Central

Davis, Brittany; Moriguchi, Takeshi; Sumpio, Bauer

2013-01-01

Although research unanimously maintains that exercise can ward off cardiovascular disease (CVD), the optimal type, duration, intensity, and combination of forms are yet not clear. In our review of existing rodent-based studies on exercise and cardiovascular health, we attempt to find the optimal forms, intensities, and durations of exercise. Using Scopus and Medline, a literature review of English language comparative journal studies of cardiovascular benefits and exercise was performed. This review examines the existing literature on rodent models of aerobic, anaerobic, and power exercise and compares the benefits of various training forms, intensities, and durations. The rodent studies reviewed in this article correlate with reports on human subjects that suggest regular aerobic exercise can improve cardiac and vascular structure and function, as well as lipid profiles, and reduce the risk of CVD. Findings demonstrate an abundance of rodent-based aerobic studies, but a lack of anaerobic and power forms of exercise, as well as comparisons of these three components of exercise. Thus, further studies must be conducted to determine a truly optimal regimen for cardiovascular health. PMID:24436579

Optimizing 4-Dimensional Magnetic Resonance Imaging Data Sampling for Respiratory Motion Analysis of Pancreatic Tumors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stemkens, Bjorn, E-mail: b.stemkens@umcutrecht.nl; Tijssen, Rob H.N.; Senneville, Baudouin D. de

2015-03-01

Purpose: To determine the optimum sampling strategy for retrospective reconstruction of 4-dimensional (4D) MR data for nonrigid motion characterization of tumor and organs at risk for radiation therapy purposes. Methods and Materials: For optimization, we compared 2 surrogate signals (external respiratory bellows and internal MRI navigators) and 2 MR sampling strategies (Cartesian and radial) in terms of image quality and robustness. Using the optimized protocol, 6 pancreatic cancer patients were scanned to calculate the 4D motion. Region of interest analysis was performed to characterize the respiratory-induced motion of the tumor and organs at risk simultaneously. Results: The MRI navigator was foundmore » to be a more reliable surrogate for pancreatic motion than the respiratory bellows signal. Radial sampling is most benign for undersampling artifacts and intraview motion. Motion characterization revealed interorgan and interpatient variation, as well as heterogeneity within the tumor. Conclusions: A robust 4D-MRI method, based on clinically available protocols, is presented and successfully applied to characterize the abdominal motion in a small number of pancreatic cancer patients.« less

The effectiveness of Teratology Information Services (TIS).

PubMed

Hancock, Rebecca L; Koren, Gideon; Einarson, Adrienne; Ungar, Wendy J

2007-02-01

Women and their health care providers have few reliable sources of information regarding the safety of exposures in pregnancy and lactation. Evidence-based information on these topics is provided by Teratology Information Services (TIS). Access to TIS, however, is limited in many regions, and many services have difficulty maintaining ongoing funding. The objective of this review is to highlight published reports of the effectiveness of TIS in improving maternal and neonatal health. A search of the Pub Med and Econ Lit databases was performed with no date restriction, using the search terms teratology, information, counseling, pregnancy, effectiveness, birth defects. Information disseminated from TIS has been shown to prevent congenital malformations, unnecessary pregnancy terminations, and occupational risks. TIS support optimal nutritional supplementation in pregnancy and optimal drug therapy in pregnancy and breast-feeding. In addition, they correct misperceptions of risk and facilitate knowledge transfer and translation. TIS have the potential to provide health care cost savings. TIS are vital services in supporting optimal maternal and neonatal health. A formal economic evaluation of TIS is required in order to inform resource allocation decision-making and continued funding of these services.

The NASA Space Radiobiology Risk Assessment Project

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; Huff, Janice; Ponomarev, Artem; Patel, Zarana; Kim, Myung-Hee

The current first phase (2006-2011) has the three major goals of: 1) optimizing the conventional cancer risk models currently used based on the double-detriment life-table and radiation quality functions; 2) the integration of biophysical models of acute radiation syndromes; and 3) the development of new systems radiation biology models of cancer processes. The first-phase also includes continued uncertainty assessment of space radiation environmental models and transport codes, and relative biological effectiveness factors (RBE) based on flight data and NSRL results, respectively. The second phase of the (2012-2016) will: 1) develop biophysical models of central nervous system risks (CNS); 2) achieve comphrensive systems biology models of cancer processes using data from proton and heavy ion studies performed at NSRL; and 3) begin to identify computational models of biological countermeasures. Goals for the third phase (2017-2021) include: 1) the development of a systems biology model of cancer risks for operational use at NASA; 2) development of models of degenerative risks, 2) quantitative models of counter-measure impacts on cancer risks; and 3) indiviudal based risk assessments. Finally, we will support a decision point to continue NSRL research in support of NASA's exploration goals beyond 2021, and create an archival of NSRL research results for continued analysis. Details on near term goals, plans for a WEB based data resource of NSRL results, and a space radiation Wikepedia are described.

The influence of dispositional optimism on post-visit anxiety and risk perception accuracy among breast cancer genetic counselees.

PubMed

Wiering, B M; Albada, A; Bensing, J M; Ausems, M G E M; van Dulmen, A M

2013-11-01

Much is unknown about the influence of dispositional optimism and affective communication on genetic counselling outcomes. This study investigated the influence of counselees' optimism on the counselees' risk perception accuracy and anxiety, while taking into account the affective communication during the first consultation for breast cancer genetic counselling. Counselees completed questionnaires measuring optimism, anxiety and the perceived risk that hereditary breast cancer runs in the family before, and anxiety and perceived risk after the first consultation. Consultations were videotaped. The duration of eye contact was measured, and verbal communication was rated using the Roter Interaction Analysis System. Less-optimistic counselees were more anxious post-visit (β = -.29; p = .00). Counsellors uttered fewer reassuring statements if counselees were more anxious (β = -.84; p = .00) but uttered more reassurance if counselees were less optimistic (β = -.76; p = .01). Counsellors expressed less empathy if counselees perceived their risk as high (β = -1.51; p = .04). An increase in the expression of reassurance was related to less post-visit anxiety (β = -.35; p = .03). More empathy was related to a greater overestimation of risk (β = .92; p = .01). Identification of a lack of optimism as a risk factor for high anxiety levels enables the adaptation of affective communication to improve genetic counselling outcomes. Because reassurance was related to less anxiety, beneficial adaptation is attainable by increasing counsellors' reassurance, if possible. Because of a lack of optimally adapted communication in this study, further research is needed to clarify how to increase counsellors' ability to adapt to counselees. Copyright © 2013 John Wiley & Sons, Ltd.

Risk-based maintenance of ethylene oxide production facilities.

PubMed

Khan, Faisal I; Haddara, Mahmoud R

2004-05-20

This paper discusses a methodology for the design of an optimum inspection and maintenance program. The methodology, called risk-based maintenance (RBM) is based on integrating a reliability approach and a risk assessment strategy to obtain an optimum maintenance schedule. First, the likely equipment failure scenarios are formulated. Out of many likely failure scenarios, the ones, which are most probable, are subjected to a detailed study. Detailed consequence analysis is done for the selected scenarios. Subsequently, these failure scenarios are subjected to a fault tree analysis to determine their probabilities. Finally, risk is computed by combining the results of the consequence and the probability analyses. The calculated risk is compared against known acceptable criteria. The frequencies of the maintenance tasks are obtained by minimizing the estimated risk. A case study involving an ethylene oxide production facility is presented. Out of the five most hazardous units considered, the pipeline used for the transportation of the ethylene is found to have the highest risk. Using available failure data and a lognormal reliability distribution function human health risk factors are calculated. Both societal risk factors and individual risk factors exceeded the acceptable risk criteria. To determine an optimal maintenance interval, a reverse fault tree analysis was used. The maintenance interval was determined such that the original high risk is brought down to an acceptable level. A sensitivity analysis is also undertaken to study the impact of changing the distribution of the reliability model as well as the error in the distribution parameters on the maintenance interval.

Do insurers respond to risk adjustment? A long-term, nationwide analysis from Switzerland.

PubMed

von Wyl, Viktor; Beck, Konstantin

2016-03-01

Community rating in social health insurance calls for risk adjustment in order to eliminate incentives for risk selection. Swiss risk adjustment is known to be insufficient, and substantial risk selection incentives remain. This study develops five indicators to monitor residual risk selection. Three indicators target activities of conglomerates of insurers (with the same ownership), which steer enrollees into specific carriers based on applicants' risk profiles. As a proxy for their market power, those indicators estimate the amount of premium-, health care cost-, and risk-adjustment transfer variability that is attributable to conglomerates. Two additional indicators, derived from linear regression, describe the amount of residual cost differences between insurers that are not covered by risk adjustment. All indicators measuring conglomerate-based risk selection activities showed increases between 1996 and 2009, paralleling the establishment of new conglomerates. At their maxima in 2009, the indicator values imply that 56% of the net risk adjustment volume, 34% of premium variability, and 51% cost variability in the market were attributable to conglomerates. From 2010 onwards, all indicators decreased, coinciding with a pre-announced risk adjustment reform implemented in 2012. Likewise, the regression-based indicators suggest that the volume and variance of residual cost differences between insurers that are not equaled out by risk adjustment have decreased markedly since 2009 as a result of the latest reform. Our analysis demonstrates that risk-selection, especially by conglomerates, is a real phenomenon in Switzerland. However, insurers seem to have reduced risk selection activities to optimize their losses and gains from the latest risk adjustment reform.

Optimization on Fc for Improvement of Stability and Aggregation Resistance.

PubMed

Chen, Xiaobo; Zeng, Fang; Huang, Tao; Cheng, Liang; Liu, Huan; Gong, Rui

2016-01-01

Fc-based therapeutics including therapeutic full-size monoclonal antibodies (mAbs) and Fcfusion proteins represent fastest-growing market in biopharmaceutical industrial. However, one major challenge during development of Fc-based therapeutics is how to maintain their efficacy in clinic use. Many factors may lead to failure in final marketing. For example, the stability and aggregation resistance might not be high enough for bearing the disadvantages during fermentation, purification, formulation, storage, shipment and other steps in manufacture and sale. Low stability and high aggregation tendency lead to decreased bioactivity and increased risk of immunogenicity resulting in serious side effect. Because Fc is one of the major parts in monoclonal antibodies and Fc-fusion proteins, engineering of Fc to increase its stability and reduce or eliminate aggregation due to incorrect association are of great importance and could further extend the potential of Fc-based therapeutics. Lots of studies focus on Fc optimization for better physical and chemical characteristics and function by structured-based computer-aid rational design, high-throughput screening expression system selection and other methods. The identification of optimized Fc mutants increases the clinic potential of currently existed therapeutics mAbs and Fc-fusion proteins, and accelerates the development of new Fc-based therapeutics. Here we provide an overview of the related field, and discuss recent advances and future directions in optimization of Fc-based therapeutics with modified stability and aggregation resistance. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Science Goals in Radiation Protection for Exploration

NASA Technical Reports Server (NTRS)

Cucinotta, Francs A.

2008-01-01

Space radiation presents major challenges to future missions to the Earth s moon or Mars. Health risks of concern include cancer, degenerative and performance risks to the central nervous system, heart and lens, and the acute radiation syndromes. The galactic cosmic rays (GCR) contain high energy and charge (HZE) nuclei, which have been shown to cause qualitatively distinct biological damage compared to terresterial radiation, such as X-rays or gamma-rays, causing risk estimates to be highly uncertain. The biological effects of solar particle events (SPE) are similar to terresterial radiation except for their biological dose-rate modifiers; however the onset and size of SPEs are difficult to predict. The high energies of GCR reduce the effectiveness of shielding, while SPE s can be shielded however the current gap in radiobiological knowledge hinders optimization. Methods used to project risks on Earth must be modified because of the large uncertainties in projecting health risks from space radiation, and thus impact mission requirements and costs. We describe NASA s unique approach to radiation safety that applies probabilistic risk assessments and uncertainty based criteria within the occupational health program for astronauts and to mission design. The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in radiation risk projection models. Exploration science goals in radiation protection are centered on ground-based research to achieve the necessary biological knowledge, and in the development of new technologies to improve SPE monitoring and optimize shielding. Radiobiology research is centered on a ground based program investigating the radiobiology of high-energy protons and HZE nuclei at the NASA Space Radiation Laboratory (NSRL) located at DoE s Brookhaven National Laboratory in Upton, NY. We describe recent NSRL results that are closing the knowledge gap in HZE radiobiology and improving exploration risk estimates. Linking probabilistic risk assessment to research goals makes it possible to express risk management objectives in terms of quantitative metrics, which include the number of days in space without exceeding a given risk level within well defined confidence limits, and probabilistic assessments of the effectiveness of design trade spaces such as material type, mass, solar cycle, crew selection criteria, and biological countermeasures. New research in SPE alert and risk assessment, individual radiation sensitivity, and biological countermeasure development are described.

Utilizing nutritional genomics to tailor diets for the prevention of cardiovascular disease: a guide for upcoming studies and implementations

USDA-ARS?s Scientific Manuscript database

Introduction: Personalized diets based on an individual's genome to optimize the success of dietary intervention and reduce genetic cardiovascular disease (CVD) risk, is one of the challenges most frequently discussed in the scientific community. Moreover, it has been widely welcomed and demanded by...

AST/R–BASED WATER REUSE AS A PART OF THE TOTAL WATER SOLUTION FOR WATER-STRESSED REGIONS: AN OVERVIEW OF ENGINEERING PRACTICE AND REGULATORY PROSPECTIVE

EPA Science Inventory

Water supply and demand are increasingly unbalanced in many parts of the world. To address the imbalance, the total water solution methodology simultaneously considers regulatory, engineering, environmental and economic factors to optimize risk management solutions for an entire...

AST/R BASED WATER REUSE AS A PART OF THE TOTAL WATER SOLUTION FOR WATER-STRESSED REGIONS: AN OVERVIEW OF ENGINEERING PRACTICE AND REGULATORY PROSPECTIVE

EPA Science Inventory

Water supply and demand are increasingly unbalanced in many parts of the world. To address the imbalance, the total water solution methodology simultaneously considers regulatory, engineering, environmental and economic factors to optimize risk management solutions for an entire ...

Building a Lasting Foundation for Promoting Protective Factors across Children's Bureau Programs

ERIC Educational Resources Information Center

Brodowski, Melissa Lim; Fischman, Lauren

2014-01-01

Over the years, various federal and non-federal organizations have disseminated and promoted a number of protective factor frameworks to reduce risk and optimize family functioning and child development. There is a growing interest in and commitment to examining factors that transcend the traditional deficit-based approach to addressing social and…

A Principle-Based Psychology of School Violence Prevention

ERIC Educational Resources Information Center

Kelley, Thomas M.; Mills, Roger C.; Shuford, Rita

2005-01-01

This paper proposes that school violence is primarily a function of the typically poor mental health of at-risk students. It asserts therefore, that the most leveraged solution to this vexing problem is for school personnel to teach these students how to re-kindle and experience their birthright of optimal psychological functioning. It suggests…

Comparative risk assessment and cessation information seeking among smokeless tobacco users.

PubMed

Jun, Jungmi; Nan, Xiaoli

2018-05-01

This research examined (1) smokeless tobacco users' comparative optimism in assessing the health and addiction risks of their own product in comparison with cigarettes, and (2) the effects of comparative optimism on cessation information-seeking. A nationally-representative sample from the 2015 Health Information National Trends Survey (HINTS)-FDA was employed. The analyses revealed the presence of comparative optimism in assessing both health and addiction risks among smokeless tobacco users. Comparative optimism was negatively correlated with most cessation information-seeking variables. Health bias (the health risk rating gap between the subject's own tobacco product and cigarettes) was associated with decreased intent to use cessation support. However, the health bias and addiction bias (the addiction risk rating gap between the subject's own tobacco product and cigarettes) were not consistent predictors of all cessation information-seeking variables, when covariates of socio-demographics and tobacco use status were included. In addition, positive correlations between health bias and past/recent cessation-information searches were observed. Optimisic biases may negatively influence cessation behaviors not only directly but also indirectly by influencing an important moderator, cessation information-seeking. Future interventions should prioritize dispelling the comparative optimism in perceiving risks of smokeless tobacco use, as well as provide more reliable cessation information specific to smokeless tobacco users. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimal H1N1 vaccination strategies based on self-interest versus group interest.

PubMed

Shim, Eunha; Meyers, Lauren Ancel; Galvani, Alison P

2011-02-25

Influenza vaccination is vital for reducing H1N1 infection-mediated morbidity and mortality. To reduce transmission and achieve herd immunity during the initial 2009-2010 pandemic season, the US Centers for Disease Control and Prevention (CDC) recommended that initial priority for H1N1 vaccines be given to individuals under age 25, as these individuals are more likely to spread influenza than older adults. However, due to significant delay in vaccine delivery for the H1N1 influenza pandemic, a large fraction of population was exposed to the H1N1 virus and thereby obtained immunity prior to the wide availability of vaccines. This exposure affects the spread of the disease and needs to be considered when prioritizing vaccine distribution. To determine optimal H1N1 vaccine distributions based on individual self-interest versus population interest, we constructed a game theoretical age-structured model of influenza transmission and considered the impact of delayed vaccination. Our results indicate that if individuals decide to vaccinate according to self-interest, the resulting optimal vaccination strategy would prioritize adults of age 25 to 49 followed by either preschool-age children before the pandemic peak or older adults (age 50-64) at the pandemic peak. In contrast, the vaccine allocation strategy that is optimal for the population as a whole would prioritize individuals of ages 5 to 64 to curb a growing pandemic regardless of the timing of the vaccination program. Our results indicate that for a delayed vaccine distribution, the priorities that are optimal at a population level do not align with those that are optimal according to individual self-interest. Moreover, the discordance between the optimal vaccine distributions based on individual self-interest and those based on population interest is even more pronounced when vaccine availability is delayed. To determine optimal vaccine allocation for pandemic influenza, public health agencies need to consider both the changes in infection risks among age groups and expected patterns of adherence.

Model-based optimization of G-CSF treatment during cytotoxic chemotherapy.

PubMed

Schirm, Sibylle; Engel, Christoph; Loibl, Sibylle; Loeffler, Markus; Scholz, Markus

2018-02-01

Although G-CSF is widely used to prevent or ameliorate leukopenia during cytotoxic chemotherapies, its optimal use is still under debate and depends on many therapy parameters such as dosing and timing of cytotoxic drugs and G-CSF, G-CSF pharmaceuticals used and individual risk factors of patients. We integrate available biological knowledge and clinical data regarding cell kinetics of bone marrow granulopoiesis, the cytotoxic effects of chemotherapy and pharmacokinetics and pharmacodynamics of G-CSF applications (filgrastim or pegfilgrastim) into a comprehensive model. The model explains leukocyte time courses of more than 70 therapy scenarios comprising 10 different cytotoxic drugs. It is applied to develop optimized G-CSF schedules for a variety of clinical scenarios. Clinical trial results showed validity of model predictions regarding alternative G-CSF schedules. We propose modifications of G-CSF treatment for the chemotherapies 'BEACOPP escalated' (Hodgkin's disease), 'ETC' (breast cancer), and risk-adapted schedules for 'CHOP-14' (aggressive non-Hodgkin's lymphoma in elderly patients). We conclude that we established a model of human granulopoiesis under chemotherapy which allows predictions of yet untested G-CSF schedules, comparisons between them, and optimization of filgrastim and pegfilgrastim treatment. As a general rule of thumb, G-CSF treatment should not be started too early and patients could profit from filgrastim treatment continued until the end of the chemotherapy cycle.

Risk management for optimal land use planning integrating ecosystem services values: A case study in Changsha, Middle China.

PubMed

Liang, Jie; Zhong, Minzhou; Zeng, Guangming; Chen, Gaojie; Hua, Shanshan; Li, Xiaodong; Yuan, Yujie; Wu, Haipeng; Gao, Xiang

2017-02-01

Land-use change has direct impact on ecosystem services and alters ecosystem services values (ESVs). Ecosystem services analysis is beneficial for land management and decisions. However, the application of ESVs for decision-making in land use decisions is scarce. In this paper, a method, integrating ESVs to balance future ecosystem-service benefit and risk, is developed to optimize investment in land for ecological conservation in land use planning. Using ecological conservation in land use planning in Changsha as an example, ESVs is regarded as the expected ecosystem-service benefit. And uncertainty of land use change is regarded as risk. This method can optimize allocation of investment in land to improve ecological benefit. The result shows that investment should be partial to Liuyang City to get higher benefit. The investment should also be shifted from Liuyang City to other regions to reduce risk. In practice, lower limit and upper limit for weight distribution, which affects optimal outcome and selection of investment allocation, should be set in investment. This method can reveal the optimal spatial allocation of investment to maximize the expected ecosystem-service benefit at a given level of risk or minimize risk at a given level of expected ecosystem-service benefit. Our results of optimal analyses highlight tradeoffs between future ecosystem-service benefit and uncertainty of land use change in land use decisions. Copyright © 2016 Elsevier B.V. All rights reserved.

Achievement of optimal medical therapy goals for U.S. adults with coronary artery disease: results from the REGARDS Study (REasons for Geographic And Racial Differences in Stroke).

PubMed

Brown, Todd M; Voeks, Jenifer H; Bittner, Vera; Brenner, David A; Cushman, Mary; Goff, David C; Glasser, Stephen; Muntner, Paul; Tabereaux, Paul B; Safford, Monika M

2014-04-29

In a nonclinical trial setting, we sought to determine the proportion of individuals with coronary artery disease (CAD) with optimal risk factor levels based on the COURAGE (Clinical Outcomes Utilizing Revascularization and Aggressive DruG Evaluation) trial. In the COURAGE trial, the addition of percutaneous coronary intervention (PCI) to optimal medical therapy did not reduce the risk of death or myocardial infarction in stable CAD patients but resulted in more revascularization procedures. The REGARDS (REasons for Geographic And Racial Differences in Stroke) study is a national prospective cohort study of 30,239 African-American and white community-dwelling individuals older than 45 years of age who enrolled in 2003 through 2007. We calculated the proportion of 3,167 participants with self-reported CAD meeting 7 risk factor goals based on the COURAGE trial: 1) aspirin use; 2) systolic blood pressure <130 mm Hg and diastolic blood pressure <85 mm Hg (<80 mm Hg if diabetic); 3) low-density lipoprotein cholesterol <85 mg/dl, high-density lipoprotein cholesterol >40 mg/dl, and triglycerides <150 mg/dl; 4) fasting glucose <126 mg/dl; 5) nonsmoking status; 6) body mass index <25 kg/m(2); and 7) exercise ≥4 days per week. The mean age of participants was 69 ± 9 years; 33% were African American and 35% were female. Overall, the median number of goals met was 4. Less than one-fourth met ≥5 of the 7 goals, and 16% met all 3 goals for aspirin, blood pressure, and low-density lipoprotein cholesterol. Older age, white race, higher income, more education, and higher physical functioning were independently associated with meeting more goals. There is substantial room for improvement in risk factor reduction among U.S. individuals with CAD. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Understanding the Cognitive and Affective Mechanisms that Underlie Proxy Risk Perceptions among Caregivers of Asthmatic Children.

PubMed

Shepperd, James A; Lipsey, Nikolette P; Pachur, Thorsten; Waters, Erika A

2018-07-01

Medical decisions made on behalf of another person-particularly those made by adult caregivers for their minor children-are often informed by the decision maker's beliefs about the treatment's risks and benefits. However, we know little about the cognitive and affective mechanisms influencing such "proxy" risk perceptions and about how proxy risk perceptions are related to prominent judgment phenomena. Adult caregivers of minor children with asthma ( N = 132) completed an online, cross-sectional survey assessing 1) cognitions and affects that form the basis of the availability, representativeness, and affect heuristics; 2) endorsement of the absent-exempt and the better-than-average effect; and 3) proxy perceived risk and unrealistic comparative optimism of an asthma exacerbation. We used the Pediatric Asthma Control and Communication Instrument (PACCI) to assess asthma severity. Respondents with higher scores on availability, representativeness, and negative affect indicated higher proxy risk perceptions and (for representativeness only) lower unrealistic optimism, irrespective of asthma severity. Conversely, respondents who showed a stronger display of the better-than-average effect indicated lower proxy risk perceptions but did not differ in unrealistic optimism. The absent-exempt effect was unrelated to proxy risk perceptions and unrealistic optimism. Heuristic judgment processes appear to contribute to caregivers' proxy risk perceptions of their child's asthma exacerbation risk. Moreover, the display of other, possibly erroneous, judgment phenomena is associated with lower caregiver risk perceptions. Designing interventions that target these mechanisms may help caregivers work with their children to reduce exacerbation risk.

Treating Youths in the Juvenile Justice System.

PubMed

Sattler, Ann L

2017-04-01

Adolescents involved with the juvenile justice system have higher rates of risky sexual behaviors, resulting in high rates of sexually transmitted infections and increased risk of human immunodeficiency virus, early or complicated pregnancy, and parenting issues. Comorbid substance abuse, gang association, mental health issues, and history of having been abused as children result in further elevated rates. Girls and lesbian, gay, bisexual, and transgender youths represent growing subpopulations with special risks. Increasingly diverted to community-based alternatives, juvenile justice-involved teens obtain most of their medical care from community providers, who need to understand their risks to provide appropriate, optimal care. Copyright © 2016 Elsevier Inc. All rights reserved.

Portfolios with fuzzy returns: Selection strategies based on semi-infinite programming

NASA Astrophysics Data System (ADS)

Vercher, Enriqueta

2008-08-01

This paper provides new models for portfolio selection in which the returns on securities are considered fuzzy numbers rather than random variables. The investor's problem is to find the portfolio that minimizes the risk of achieving a return that is not less than the return of a riskless asset. The corresponding optimal portfolio is derived using semi-infinite programming in a soft framework. The return on each asset and their membership functions are described using historical data. The investment risk is approximated by mean intervals which evaluate the downside risk for a given fuzzy portfolio. This approach is illustrated with a numerical example.

A single-center experience and review of the literature: 64 cases of phyllodes tumors to better understand risk factors and disease management.

PubMed

Lightner, Amy L; Shurell, Elizabeth; Dawson, Nicole; Omidvar, Yasaman; Foster, Nova

2015-03-01

Phyllodes tumors of the breast are rare fibroepithelial tumors that are characterized as benign, borderline, or malignant based on cellular characteristics such as stromal overgrowth and number of mitoses. Currently, there is a lack of consensus on risk factors and management of patients with phyllodes tumors, which has led to variation in treatment patterns as well as patient outcomes across many institutions. This study seeks to understand the clinicopathologic features, risk factors for local and metastatic recurrence, and clinical outcomes of patients with phyllodes tumors to better define optimal treatment patterns.

Resilient parenting of preschool children at developmental risk.

PubMed

Ellingsen, R; Baker, B L; Blacher, J; Crnic, K

2014-07-01

Given the great benefits of effective parenting to child development under normal circumstances, and the even greater benefits in the face of risk, it is important to understand why some parents manage to be effective in their interactions with their child despite facing formidable challenges. This study examined factors that promoted effective parenting in the presence of child developmental delay, high child behaviour problems, and low family income. Data were obtained from 232 families at child age 3 and 5 years. Using an adapted ABCX model, we examined three risk domains (child developmental delay, child behaviour problems, and low family income) and three protective factors (mother's education, health, and optimism). The outcome of interest was positive parenting as coded from mother-child interactions. Levels of positive parenting differed across levels of risk. Education and optimism appeared to be protective factors for positive parenting at ages 3 and 5, and health appeared to be an additional protective factor at age 5. There was an interaction between risk and education at age 3; mothers with higher education engaged in more positive parenting at higher levels of risk than did mothers with less education. There was also an interaction between risk and optimism at age 3; mothers with higher optimism engaged in more positive parenting at lower levels of risk than did mothers with less optimism. The risk index did not predict change in positive parenting from age 3-5, but the protective factor of maternal health predicted positive changes. This study examined factors leading to positive parenting in the face of risk, a topic that has received less attention in the literature on disability. Limitations, future directions, and implications for intervention are discussed. © 2013 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

NASA Technical Reports Server (NTRS)

Arellano, John; Young, M.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Goodenow, D. A.; Myers, J. G.

2016-01-01

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

The influence of the free space environment on the superlight-weight thermal protection system: conception, methods, and risk analysis

NASA Astrophysics Data System (ADS)

Yatsenko, Vitaliy; Falchenko, Iurii; Fedorchuk, Viktor; Petrushynets, Lidiia

2016-07-01

This report focuses on the results of the EU project "Superlight-weight thermal protection system for space application (LIGHT-TPS)". The bottom line is an analysis of influence of the free space environment on the superlight-weight thermal protection system (TPS). This report focuses on new methods that based on the following models: synergetic, physical, and computational. This report concentrates on four approaches. The first concerns the synergetic approach. The synergetic approach to the solution of problems of self-controlled synthesis of structures and creation of self-organizing technologies is considered in connection with the super-problem of creation of materials with new functional properties. Synergetics methods and mathematical design are considered according to actual problems of material science. The second approach describes how the optimization methods can be used to determine material microstructures with optimized or targeted properties. This technique enables one to find unexpected microstructures with exotic behavior (e.g., negative thermal expansion coefficients). The third approach concerns the dynamic probabilistic risk analysis of TPS l elements with complex characterizations for damages using a physical model of TPS system and a predictable level of ionizing radiation and space weather. Focusing is given mainly on the TPS model, mathematical models for dynamic probabilistic risk assessment and software for the modeling and prediction of the influence of the free space environment. The probabilistic risk assessment method for TPS is presented considering some deterministic and stochastic factors. The last approach concerns results of experimental research of the temperature distribution on the surface of the honeycomb sandwich panel size 150 x 150 x 20 mm at the diffusion welding in vacuum are considered. An equipment, which provides alignment of temperature fields in a product for the formation of equal strength of welded joints is considered. Many tasks in computational materials science can be posed as optimization problems. This technique enables one to find unexpected microstructures with exotic behavior (e.g., negative thermal expansion coefficients). The last approach is concerned with the generation of realizations of materials with specified but limited microstructural information: an intriguing inverse problem of both fundamental and practical importance. Computational models based upon the theories of molecular dynamics or quantum mechanics would enable the prediction and modification of fundamental materials properties. This problem is solved using deterministic and stochastic optimization techniques. The main optimization approaches in the frame of the EU project "Superlight-weight thermal protection system for space application" are discussed. Optimization approach to the alloys for obtaining materials with required properties using modeling techniques and experimental data will be also considered. This report is supported by the EU project "Superlight-weight thermal protection system for space application (LIGHT-TPS)"

Optimal Waist-to-Height Ratio Values for Cardiometabolic Risk Screening in an Ethnically Diverse Sample of South African Urban and Rural School Boys and Girls

PubMed Central

Matsha, Tandi E.; Kengne, Andre-Pascal; Yako, Yandiswa Y.; Hon, Gloudina M.; Hassan, Mogamat S.; Erasmus, Rajiv T.

2013-01-01

Background The proposed waist-to-height ratio (WHtR) cut-off of 0.5 is less optimal for cardiometabolic risk screening in children in many settings. The purpose of this study was to determine the optimal WHtR for children from South Africa, and investigate variations by gender, ethnicity and residence in the achieved value. Methods Metabolic syndrome (MetS) components were measured in 1272 randomly selected learners, aged 10–16 years, comprising of 446 black Africans, 696 mixed-ancestry and 130 Caucasians. The Youden’s index and the closest-top-left (CTL) point approaches were used to derive WHtR cut-offs for diagnosing any two MetS components, excluding the waist circumference. Results The two approaches yielded similar cut-off in girls, 0.465 (sensitivity 50.0, specificity 69.5), but two different values in boys, 0.455 (42.9, 88.4) and 0.425 (60.3, 67.7) based on the Youden’s index and the CTL point, respectively. Furthermore, WHtR cut-off values derived differed substantially amongst the regions and ethnic groups investigated, whereby the highest cut-off was observed in semi-rural and white children, respectively, Youden’s index0.505 (31.6, 87.1) and CTL point 0.475 (44.4, 75.9). Conclusion The WHtR cut-off of 0.5 is less accurate for screening cardiovascular risk in South African children. The optimal value in this setting is likely gender and ethnicity-specific and sensitive to urbanization. PMID:23967160

Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; George, K.; Hu, X.; Kim, M. H.; Nikjoo, H.

2006-01-01

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Managing Space Radiation Risks On Lunar and Mars Missions: Risk Assessment and Mitigation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; George, K.; Hu, X.; Kim, M. H.; Nikjoo, H.

2005-01-01

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Managing Space Radiation Risks on Lunar and Mars Missions: Risk Assessment and Mitigation

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; George, K.; Hu, X.; Kim, M. H.; Nikjoo, H.; Ponomarev, A.; Ren, L.; Shavers, M. R.; Wu, H.

2005-01-01

Radiation-induced health risks are a primary concern for human exploration outside the Earth's magnetosphere, and require improved approaches to risk estimation and tools for mitigation including shielding and biological countermeasures. Solar proton events are the major concern for short-term lunar missions (<60 d), and for long-term missions (>60 d) such as Mars exploration, the exposures to the high energy and charge (HZE) ions that make-up the galactic cosmic rays are the major concern. Health risks from radiation exposure are chronic risks including carcinogenesis and degenerative tissue risks, central nervous system effects, and acute risk such as radiation sickness or early lethality. The current estimate is that a more than four-fold uncertainty exists in the projection of lifetime mortality risk from cosmic rays, which severely limits analysis of possible benefits of shielding or biological countermeasure designs. Uncertainties in risk projections are largely due to insufficient knowledge of HZE ion radiobiology, which has led NASA to develop a unique probabilistic approach to radiation protection. We review NASA's approach to radiation risk assessment including its impact on astronaut dose limits and application of the ALARA (As Low as Reasonably Achievable) principle. The recently opened NASA Space Radiation Laboratory (NSRL) provides the capability to simulate the cosmic rays in controlled ground-based experiments with biological and shielding models. We discuss how research at NSRL will lead to reductions in the uncertainties in risk projection models. In developing mission designs, the reduction of health risks and mission constraints including costs are competing concerns that need to be addressed through optimization procedures. Mitigating the risks from space radiation is a multi-factorial problem involving individual factors (age, gender, genetic makeup, and exposure history), operational factors (planetary destination, mission length, and period in the solar cycle), and shielding characteristics (materials, mass, and topology). We review optimization metrics for radiation protection including scenarios that integrate biophysics models of radiation risks, operational variables, and shielding design tools needed to assess exploration mission designs. We discuss the application of a crosscutting metric, based on probabilistic risk assessment, to lunar and Mars mission trade studies including the assessment of multi-factorial problems and the potential benefits of new radiation health research strategies or mitigation technologies.

Risk-Based Approach for Microbiological Food Safety Management in the Dairy Industry: The Case of Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk.

PubMed

Tenenhaus-Aziza, Fanny; Daudin, Jean-Jacques; Maffre, Alexandre; Sanaa, Moez

2014-01-01

According to Codex Alimentarius Commission recommendations, management options applied at the process production level should be based on good hygiene practices, HACCP system, and new risk management metrics such as the food safety objective. To follow this last recommendation, the use of quantitative microbiological risk assessment is an appealing approach to link new risk-based metrics to management options that may be applied by food operators. Through a specific case study, Listeria monocytogenes in soft cheese made from pasteurized milk, the objective of the present article is to practically show how quantitative risk assessment could be used to direct potential intervention strategies at different food processing steps. Based on many assumptions, the model developed estimates the risk of listeriosis at the moment of consumption taking into account the entire manufacturing process and potential sources of contamination. From pasteurization to consumption, the amplification of a primo-contamination event of the milk, the fresh cheese or the process environment is simulated, over time, space, and between products, accounting for the impact of management options, such as hygienic operations and sampling plans. A sensitivity analysis of the model will help orientating data to be collected prioritarily for the improvement and the validation of the model. What-if scenarios were simulated and allowed for the identification of major parameters contributing to the risk of listeriosis and the optimization of preventive and corrective measures. © 2013 Society for Risk Analysis.

Thrombophilia testing has limited usefulness in clinical decision-making and should be used selectively.

PubMed

Masuda, Elna M; Lee, Raymond W; Okazaki, Ian J; Benyamini, Pouya; Kistner, Robert L

2015-04-01

Management of venous thromboembolism (VTE) includes evaluation for hypercoagulable state, especially if the VTE occurs in young patients, is recurrent, or is associated with a positive family history. These laboratory tests are costly, and surprisingly, there is little evidence showing that testing leads to improved clinical outcomes. Evidence based on observational prospective studies suggests that optimal duration of anticoagulation should be based on clinical risks resulting in VTE, such as transient, permanent, and idiopathic or unprovoked risks, and less on abnormal thrombophilia values. Thrombophilia screening is important in a subgroup of clinical scenarios, such as when there is clinical suspicion of antiphospholipid antibody syndrome, heparin resistance, or warfarin necrosis; with thrombosis occurring in unusual sites (such as mesenteric or cerebral deep venous thrombosis); and for pregnant women or those seeking pregnancy or considering estrogen-based agents. Thrombophilia screening is not likely to be helpful in most cases of first-time unprovoked VTE in the setting of transient risks, active malignant disease, deep venous thrombosis of upper extremity veins or from central lines, two or more VTEs, or arterial thrombosis with pre-existing atherosclerotic risk factors. The desire by both patient and physician for a scientific explanation of the clotting event may alone lead to testing, and if so, it should be with the understanding that an abnormal test result will likely not change management, and normal results do not accurately exclude a thrombophilic defect because there are likely factors yet to be discovered. Such false assumptions may lead to shorter durations of treatment than are optimal. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Genetic Algorithm-Based Optimization to Match Asteroid Energy Deposition Curves

NASA Technical Reports Server (NTRS)

Tarano, Ana; Mathias, Donovan; Wheeler, Lorien; Close, Sigrid

2018-01-01

An asteroid entering Earth's atmosphere deposits energy along its path due to thermal ablation and dissipative forces that can be measured by ground-based and spaceborne instruments. Inference of pre-entry asteroid properties and characterization of the atmospheric breakup is facilitated by using an analytic fragment-cloud model (FCM) in conjunction with a Genetic Algorithm (GA). This optimization technique is used to inversely solve for the asteroid's entry properties, such as diameter, density, strength, velocity, entry angle, and strength scaling, from simulations using FCM. The previous parameters' fitness evaluation involves minimizing error to ascertain the best match between the physics-based calculated energy deposition and the observed meteors. This steady-state GA provided sets of solutions agreeing with literature, such as the meteor from Chelyabinsk, Russia in 2013 and Tagish Lake, Canada in 2000, which were used as case studies in order to validate the optimization routine. The assisted exploration and exploitation of this multi-dimensional search space enables inference and uncertainty analysis that can inform studies of near-Earth asteroids and consequently improve risk assessment.

Using multiscale texture and density features for near-term breast cancer risk analysis

PubMed Central

Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

2015-01-01

Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038

Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+ patients.

PubMed

Head, Linden; Nessim, Carolyn; Usher Boyd, Kirsty

2017-02-01

Bilateral prophylactic mastectomy (BPM) has demonstrated breast cancer risk reduction in high-risk/ BRCA + patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency. We retrospectively reviewed the cases of all high-risk/ BRCA + patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1-2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/ BRCA + status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared. There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model ( p = 0.003, p < 0.001 and p = 0.015, respectively). A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization.

Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+ patients

PubMed Central

Head, Linden; Nessim, Carolyn; Boyd, Kirsty Usher

2017-01-01

Background Bilateral prophylactic mastectomy (BPM) has shown breast cancer risk reduction in high-risk/BRCA+ patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency. Methods We retrospectively reviewed the cases of all high-risk/BRCA+ patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1–2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/BRCA+ status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared. Results There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model (p = 0.003, p < 0.001 and p = 0.015, respectively). Conclusion A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization. PMID:28234588

Innovative practice model to optimize resource utilization and improve access to care for high-risk and BRCA+ patients.

PubMed

Head, Linden; Nessim, Carolyn; Usher Boyd, Kirsty

2016-12-01

Bilateral prophylactic mastectomy (BPM) has demonstrated breast cancer risk reduction in high-risk/ BRCA + patients. However, priority of active cancers coupled with inefficient use of operating room (OR) resources presents challenges in offering BPM in a timely manner. To address these challenges, a rapid access prophylactic mastectomy and immediate reconstruction (RAPMIR) program was innovated. The purpose of this study was to evaluate RAPMIR with regards to access to care and efficiency. We retrospectively reviewed the cases of all high-risk/ BRCA + patients having had BPM between September 2012 and August 2014. Patients were divided into 2 groups: those managed through the traditional model and those managed through the RAPMIR model. RAPMIR leverages 2 concurrently running ORs with surgical oncology and plastic surgery moving between rooms to complete 3 combined BPMs with immediate reconstruction in addition to 1-2 independent cases each operative day. RAPMIR eligibility criteria included high-risk/ BRCA + status; BPM with immediate, implant-based reconstruction; and day surgery candidacy. Wait times, case volumes and patient throughput were measured and compared. There were 16 traditional patients and 13 RAPMIR patients. Mean wait time (days from referral to surgery) for RAPMIR was significantly shorter than for the traditional model (165.4 v. 309.2 d, p = 0.027). Daily patient throughput (4.3 v. 2.8), plastic surgery case volume (3.7 v. 1.6) and surgical oncology case volume (3.0 v. 2.2) were significantly greater in the RAPMIR model than the traditional model ( p = 0.003, p < 0.001 and p = 0.015, respectively). A multidisciplinary model with optimized scheduling has the potential to improve access to care and optimize resource utilization.

Flexible modulation of risk attitude during decision-making under quota.

PubMed

Fujimoto, Atsushi; Takahashi, Hidehiko

2016-10-01

Risk attitude is often regarded as an intrinsic parameter in the individual personality. However, ethological studies reported state-dependent strategy optimization irrespective of individual preference. To synthesize the two contrasting literatures, we developed a novel gambling task that dynamically manipulated the quota severity (required outcome to clear the task) in a course of choice trials and conducted a task-fMRI study in human participants. The participants showed their individual risk preference when they had no quota constraint ('individual-preference mode'), while they adopted state-dependent optimal strategy when they needed to achieve a quota ('strategy-optimization mode'). fMRI analyses illustrated that the interplay among prefrontal areas and salience-network areas reflected the quota severity and the utilization of the optimal strategy, shedding light on the neural substrates of the quota-dependent risk attitude. Our results demonstrated the complex nature of risk-sensitive decision-making and may provide a new perspective for the understanding of problematic risky behaviors in human. Copyright © 2016 Elsevier Inc. All rights reserved.

Cardiovascular disease risk factors in a Nigerian population with impaired fasting blood glucose level and diabetes mellitus.

PubMed

Oguoma, Victor M; Nwose, Ezekiel U; Ulasi, Ifeoma I; Akintunde, Adeseye A; Chukwukelu, Ekene E; Bwititi, Phillip T; Richards, Ross S; Skinner, Timothy C

2017-01-06

Diabetes is a risk factor for cardiovascular diseases (CVDs) and there are reports of increasing prevalence of prediabetes in Nigeria. This study therefore characterised CVDs risk factors in subjects with impaired fasting glucose (IFG) and diabetes. Data from 4 population-based cross-sectional studies on 2447 apparently healthy individuals from 18 - 89 years were analysed. Anthropometric, blood pressure and biochemical parameters were collected and classified. Individuals with IFG (prediabetes) and diabetes were merged each for positive cases of dyslipidaemia, high blood pressure (HBP) or obesity. Optimal Discriminant and Hierarchical Optimal Classification Tree Analysis (HO-CTA) were employed. Overall prevalence of IFG and diabetes were 5.8% (CI: 4.9 - 6.7%) and 3.1% (CI: 2.4 - 3.8%), respectively. IFG co-morbidity with dyslipidaemia (5.0%; CI: 4.1 - 5.8%) was the highest followed by overweight/obese (3.1%; CI: 2.5 - 3.8%) and HBP (1.8%; CI: 1.3 - 2.4%). The predicted age of IFG or diabetes and their co-morbidity with other CVD risk factors were between 40 - 45 years. Elevated blood level of total cholesterol was the most predictive co-morbid risk factor among IFG and diabetes subjects. Hypertriglyceridaemia was an important risk factor among IFG-normocholesterolaemic-overweight/obese individuals. The higher prevalence of co-morbidity of CVD risk factors with IFG than in diabetes plus the similar age of co-morbidity between IFG and diabetes highlights the need for risk assessment models for prediabetes and education of individuals at risk about factors that mitigate development of diabetes and CVDs.

Water-Energy-Food Nexus in Asia-Pacific Ring of Fire

NASA Astrophysics Data System (ADS)

Taniguchi, M.; Endo, A.; Gurdak, J. J.; Allen, D. M.; Siringan, F.; Delinom, R.; Shoji, J.; Fujii, M.; Baba, K.

2013-12-01

Climate change and economic development are causing increased pressure on water, energy and food resources, presenting communities with increased levels of tradeoffs and potential conflicts among these resources. Therefore, the water-energy-food nexus is one of the most important and fundamental global environmental issues facing the world. For the purposes of this research project, we define human-environmental security as the joint optimization between human and environmental security as well as the water-energy-food nexus. To optimize the governance and management within these inter-connected needs, it is desirable to increase human-environmental security by improving social managements for the water-energy-food nexus. In this research project, we intend to establish a method to manage and optimize the human-environmental security of the water-energy-food nexus by using integrated models, indices, and maps as well as social and natural investigations with stakeholder analyses. We base our approach on the viewpoint that it is important for a sustainable society to increase human-environmental security with decreasing risk and increasing resilience by optimizing the connections within the critical water-energy and water-food clusters. We will take a regional perspective to address these global environmental problems. The geological and geomorphological conditions in our proposed study area are heavily influenced by the so-called 'Ring of Fire,' around the Pacific Ocean. Within these areas including Japan and Southeast Asia, the hydro-meteorological conditions are dominated by the Asia monsoon. The populations that live under these natural conditions face elevated risk and potential disaster as negative impacts, while also benefitting from positive ecological goods and services. There are therefore tradeoffs and conflicts within the water-energy-food nexus, as well as among various stakeholders in the region. The objective of this project is to maximize human-environmental security (minimize the risk) by choosing management structures and policies that optimize both the water-food-energy nexus in Asia-Pacific coastal regions. We define joint security approach as optimized policy. Optimal policies will develop joint security approaches for human-environmental security in the coastal region of the Ring of Fire, including stakeholders and decision-makers.

A Method for the Selection of Exploration Areas for Unconformity Uranium Deposits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harris, DeVerle P.; Zaluski, Gerard; Marlatt, James

2009-06-15

The method we propose employs two analyses: (1) exploration simulation and risk valuation and (2) portfolio optimization. The first analysis, implemented by the investment worth system (IWS), uses Monte Carlo simulation to integrate a wide spectrum of uncertain and varied components to a relative frequency histogram for net present value of the exploration investment, which is converted to a risk-adjusted value (RAV). Iterative rerunning of the IWS enables the mapping of the relationship of RAV to magnitude of exploration expenditure, X. The second major analysis uses RAV vs. X maps to identify that subset (portfolio) of areas that maximizes themore » RAV of the firm's multiyear exploration budget. The IWS, which is demonstrated numerically, consists of six components based on the geologic description of a hypothetical basin and project area (PA) and a mix of hypothetical and actual conditions of an unidentified area. The geology is quantified and processed by Bayesian belief networks to produce the geology-based inputs required by the IWS. An exploration investment of $60 M produced a highly skewed distribution of net present value (NPV), having mean and median values of $4,160 M and $139 M, respectively. For hypothetical mining firm Minex, the RAV of the exploration investment of $60 M is only $110.7 M. An RAV that is less than 3% of mean NPV reflects the aversion by Minex to risk as well as the magnitude of risk implicit to the highly skewed NPV distribution and the probability of 0.45 for capital loss. Potential benefits of initiating exploration of a portfolio of areas, as contrasted with one area, include increased marginal productivity of exploration as well as reduced probability for nondiscovery. For an exogenously determined multiyear exploration budget, a conceptual framework for portfolio optimization is developed based on marginal RAV exploration products for candidate PAs. PORTFOLIO, a software developed to implement optimization, allocates exploration to PAs so that the RAV of the exploration budget is maximized. Moreover, PORTFOLIO provides a means to examine the impact of magnitude of budget on the composition of the exploration portfolio and the optimum allocation of exploration to PAs that comprise the portfolio. Using fictitious data for five PAs, a numerical demonstration is provided of the use of PORTFOLIO to identify those PAs that comprise the optimum exploration portfolio and to optimally allocate the multiyear budget across portfolio PAs.« less

Understanding Engagement in HIV Risk and Prevention Research Among Black Young Men Who Have Sex with Men and Transgender Women in the District of Columbia

PubMed Central

Houston, Ebony; Peterson, James; Kuo, Irene; Magnus, Manya

2016-01-01

Abstract Purpose: To develop optimal methods to study sexual health among black young men who have sex with men and transgender women (BYMSM/TW). Methods: We conducted a mixed-methods prospective study to identify recruitment and retention strategies for BYMSM/TW (age 16–21) in Washington D.C., and describe HIV risk behaviors and context. Results: Incentivized peer referral was highly productive, and 60% of BYMSM/TW were retained for 3 months. Participants reported high levels of sexual risk, homophobia, racism, and maternal support. Conclusion: BYMSM/TW studies should utilize a combination of peer-based, in-person, and technology-based recruiting strategies. Additional research is needed to leverage mobile technology and social media to enhance retention. PMID:26651365

Optimizing critical source control of five priority-regulatory trace elements from industrial wastewater in China: Implications for health management.

PubMed

Wu, Wenjun; Wang, Jinnan; Yu, Yang; Jiang, Hongqiang; Liu, Nianlei; Bi, Jun; Liu, Miaomiao

2018-04-01

Anthropogenic emissions of toxic trace elements (TEs) have caused worldwide concern due to their adverse effects on human health and ecosystems. Based on a stochastic simulation of factors' probability distribution, we established a bottom-up model to estimate the amounts of five priority-regulatory TEs released to aquatic environments from industrial processes in China. Total TE emissions in China in 2010 were estimated at approximately 2.27 t of Hg, 310.09 t of As, 318.17 t of Pb, 79.72 t of Cd, and 1040.32 t of Cr. Raw chemicals, smelting, and mining were the leading sources of TE emissions. There are apparent regional differences in TE pollution. TE emissions are much higher in eastern and central China than in the western provinces and are higher in the south than in the north. This spatial distribution was characterized in detail by allocating the emissions to 10 km × 10 km grid cells. Furthermore, the risk control for the overall emission grid was optimized according to each cell's emission and risk rank. The results show that to control 80% of TE emissions from major sources, the number of top-priority control cells would be between 200 and 400, and less than 10% of the total population would be positively affected. Based on TE risk rankings, decreasing the population weighted risk would increase the number of controlled cells by a factor of 0.3-0.5, but the affected population would increase by a factor of 0.8-1.5. In this case, the adverse effects on people's health would be reduced significantly. Finally, an optimized strategy to control TE emissions is proposed in terms of a cost-benefit trade-off. The estimates in this paper can be used to help establish a regional TE inventory and cyclic simulation, and it can also play supporting roles in minimizing TE health risks and maximizing resilience. Copyright © 2018 Elsevier Ltd. All rights reserved.

Integration of tobacco cessation services into multidisciplinary lung cancer care: rationale, state of the art, and future directions

PubMed Central

Warren, Graham W.

2015-01-01

Tobacco use is the largest risk factor for lung cancer and many lung cancer patients still smoke at the time of diagnosis. Although clinical practice guidelines recommend that all patients receive evidence-based tobacco treatment, implementation of these services in oncology practices is inconsistent and inadequate. Multidisciplinary lung cancer treatment programs offer an ideal environment to optimally deliver effective smoking cessation services. This article reviews best practice recommendations and current status of tobacco treatment for oncology patients, and provides recommendations to optimize delivery of tobacco treatment in multidisciplinary practice. PMID:26380175

NASA's Human Mission to a Near-Earth Asteroid: Landing on a Moving Target

NASA Technical Reports Server (NTRS)

Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.

2011-01-01

This paper describes a Bayesian approach for comparing the productivity and cost-risk tradeoffs of sending versus not sending one or more robotic surveyor missions prior to a human mission to land on an asteroid. The expected value of sample information based on productivity combined with parametric variations in the prior probability an asteroid might be found suitable for landing were used to assess the optimal number of spacecraft and asteroids to survey. The analysis supports the value of surveyor missions to asteroids and indicates one launch with two spacecraft going simultaneously to two independent asteroids appears optimal.

Goal-oriented Site Characterization in Hydrogeological Applications: An Overview

NASA Astrophysics Data System (ADS)

Nowak, W.; de Barros, F.; Rubin, Y.

2011-12-01

In this study, we address the importance of goal-oriented site characterization. Given the multiple sources of uncertainty in hydrogeological applications, information needs of modeling, prediction and decision support should be satisfied with efficient and rational field campaigns. In this work, we provide an overview of an optimal sampling design framework based on Bayesian decision theory, statistical parameter inference and Bayesian model averaging. It optimizes the field sampling campaign around decisions on environmental performance metrics (e.g., risk, arrival times, etc.) while accounting for parametric and model uncertainty in the geostatistical characterization, in forcing terms, and measurement error. The appealing aspects of the framework lie on its goal-oriented character and that it is directly linked to the confidence in a specified decision. We illustrate how these concepts could be applied in a human health risk problem where uncertainty from both hydrogeological and health parameters are accounted.

Optimizing noise control strategy in a forging workshop.

PubMed

Razavi, Hamideh; Ramazanifar, Ehsan; Bagherzadeh, Jalal

2014-01-01

In this paper, a computer program based on a genetic algorithm is developed to find an economic solution for noise control in a forging workshop. Initially, input data, including characteristics of sound sources, human exposure, abatement techniques, and production plans are inserted into the model. Using sound pressure levels at working locations, the operators who are at higher risk are identified and picked out for the next step. The program is devised in MATLAB such that the parameters can be easily defined and changed for comparison. The final results are structured into 4 sections that specify an appropriate abatement method for each operator and machine, minimum allowance time for high-risk operators, required damping material for enclosures, and minimum total cost of these treatments. The validity of input data in addition to proper settings in the optimization model ensures the final solution is practical and economically reasonable.

Dispositional optimism, self-framing and medical decision-making.

PubMed

Zhao, Xu; Huang, Chunlei; Li, Xuesong; Zhao, Xin; Peng, Jiaxi

2015-03-01

Self-framing is an important but underinvestigated area in risk communication and behavioural decision-making, especially in medical settings. The present study aimed to investigate the relationship among dispositional optimism, self-frame and decision-making. Participants (N = 500) responded to the Life Orientation Test-Revised and self-framing test of medical decision-making problem. The participants whose scores were higher than the middle value were regarded as highly optimistic individuals. The rest were regarded as low optimistic individuals. The results showed that compared to the high dispositional optimism group, participants from the low dispositional optimism group showed a greater tendency to use negative vocabulary to construct their self-frame, and tended to choose the radiation therapy with high treatment survival rate, but low 5-year survival rate. Based on the current findings, it can be concluded that self-framing effect still exists in medical situation and individual differences in dispositional optimism can influence the processing of information in a framed decision task, as well as risky decision-making. © 2014 International Union of Psychological Science.

Library-based illumination synthesis for critical CMOS patterning.

PubMed

Yu, Jue-Chin; Yu, Peichen; Chao, Hsueh-Yung

2013-07-01

In optical microlithography, the illumination source for critical complementary metal-oxide-semiconductor layers needs to be determined in the early stage of a technology node with very limited design information, leading to simple binary shapes. Recently, the availability of freeform sources permits us to increase pattern fidelity and relax mask complexities with minimal insertion risks to the current manufacturing flow. However, source optimization across many patterns is often treated as a design-of-experiments problem, which may not fully exploit the benefits of a freeform source. In this paper, a rigorous source-optimization algorithm is presented via linear superposition of optimal sources for pre-selected patterns. We show that analytical solutions are made possible by using Hopkins formulation and quadratic programming. The algorithm allows synthesized illumination to be linked with assorted pattern libraries, which has a direct impact on design rule studies for early planning and design automation for full wafer optimization.

Using Fuzzy Analytic Hierarchy Process multicriteria and Geographical information system for coastal vulnerability analysis in Morocco: The case of Mohammedia

NASA Astrophysics Data System (ADS)

Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha

2016-04-01

This paper shows a method to assess the vulnerability of coastal risks such as coastal erosion or submarine applying Fuzzy Analytic Hierarchy Process (FAHP) and spatial analysis techniques with Geographic Information System (GIS). The coast of the Mohammedia located in Morocco was chosen as the study site to implement and validate the proposed framework by applying a GIS-FAHP based methodology. The coastal risk vulnerability mapping follows multi-parametric causative factors as sea level rise, significant wave height, tidal range, coastal erosion, elevation, geomorphology and distance to an urban area. The Fuzzy Analytic Hierarchy Process methodology enables the calculation of corresponding criteria weights. The result shows that the coastline of the Mohammedia is characterized by a moderate, high and very high level of vulnerability to coastal risk. The high vulnerability areas are situated in the east at Monika and Sablette beaches. This technical approach is based on the efficiency of the Geographic Information System tool based on Fuzzy Analytical Hierarchy Process to help decision maker to find optimal strategies to minimize coastal risks.

Debiasing comparative optimism and increasing worry for health outcomes.

PubMed

Rose, Jason P

2012-11-01

Comparative optimism - feeling at less personal risk for negative outcomes than one's peers - has been linked to reduced prevention efforts. This study examined a novel debiasing technique aimed at simultaneously reducing both indirectly and directly measured comparative optimism. Before providing direct comparative estimates, participants provided absolute self and peer estimates in a joint format (same computer screen) or a separate format (different computer screens). Relative to the separate format condition, participants in the joint format condition showed (1) lower comparative optimism in absolute/indirect measures, (2) lower direct comparative optimism, and (3) heightened worry. Implications for risk perception screening are discussed.

Mechanistic analysis of Zein nanoparticles/PLGA triblock in situ forming implants for glimepiride.

PubMed

Ahmed, Osama Abdelhakim Aly; Zidan, Ahmed Samir; Khayat, Maan

2016-01-01

The study aims at applying pharmaceutical nanotechnology and D-optimal fractional factorial design to screen and optimize the high-risk variables affecting the performance of a complex drug delivery system consisting of glimepiride-Zein nanoparticles and inclusion of the optimized formula with thermoresponsive triblock copolymers in in situ gel. Sixteen nanoparticle formulations were prepared by liquid-liquid phase separation method according to the D-optimal fractional factorial design encompassing five variables at two levels. The responses investigated were glimepiride entrapment capacity (EC), particle size and size distribution, zeta potential, and in vitro drug release from the prepared nanoparticles. Furthermore, the feasibility of embedding the optimized Zein-based glimepiride nanoparticles within thermoresponsive triblock copolymers poly(lactide-co-glycolide)-block-poly(ethylene glycol)-block-poly(lactide-co-glycolide) in in situ gel was evaluated for controlling glimepiride release rate. Through the systematic optimization phase, improvement of glimepiride EC of 33.6%, nanoparticle size of 120.9 nm with a skewness value of 0.2, zeta potential of 11.1 mV, and sustained release features of 3.3% and 17.3% drug released after 2 and 24 hours, respectively, were obtained. These desirability functions were obtained at Zein and glimepiride loadings of 50 and 75 mg, respectively, utilizing didodecyldimethylammonium bromide as a stabilizer at 0.1% and 90% ethanol as a common solvent. Moreover, incorporating this optimized formulation in triblock copolymers-based in situ gel demonstrated pseudoplastic behavior with reduction of drug release rate as the concentration of polymer increased. This approach to control the release of glimepiride using Zein nanoparticles/triblock copolymers-based in situ gel forming intramuscular implants could be useful for improving diabetes treatment effectiveness.

Irrigation, risk aversion, and water right priority under water supply uncertainty

PubMed Central

Xu, Wenchao; Rosegrant, Mark W.

2017-01-01

Abstract This paper explores the impacts of a water right's allocative priority—as an indicator of farmers' risk‐bearing ability—on land irrigation under water supply uncertainty. We develop and use an economic model to simulate farmers' land irrigation decision and associated economic returns in eastern Idaho. Results indicate that the optimal acreage of land irrigated increases with water right priority when hydroclimate risk exhibits a negatively skewed or right‐truncated distribution. Simulation results suggest that prior appropriation enables senior water rights holders to allocate a higher proportion of their land to irrigation, 6 times as much as junior rights holders do, creating a gap in the annual expected net revenue reaching up to $141.4 acre−1 or $55,800 per farm between the two groups. The optimal irrigated acreage, expected net revenue, and shadow value of a water right's priority are subject to substantial changes under a changing climate in the future, where temporal variation in water supply risks significantly affects the profitability of agricultural land use under the priority‐based water sharing mechanism. PMID:29200529

Challenges and solutions in medically managed ACS in the Asia-Pacific region: expert recommendations from the Asia-Pacific ACS Medical Management Working Group.

PubMed

Huo, Yong; Thompson, Peter; Buddhari, Wacin; Ge, Junbo; Harding, Scott; Ramanathan, Letchuman; Reyes, Eugenio; Santoso, Anwar; Tam, Li-Wah; Vijayaraghavan, Govindan; Yeh, Hung-I

2015-03-15

Acute coronary syndromes (ACS) remain a leading cause of mortality and morbidity in the Asia-Pacific (APAC) region. International guidelines advocate invasive procedures in all but low-risk ACS patients; however, a high proportion of ACS patients in the APAC region receive solely medical management due to a combination of unique geographical, socioeconomic, and population-specific barriers. The APAC ACS Medical Management Working Group recently convened to discuss the ACS medical management landscape in the APAC region. Local and international ACS guidelines and the global and APAC clinical evidence-base for medical management of ACS were reviewed. Challenges in the provision of optimal care for these patients were identified and broadly categorized into issues related to (1) accessibility/systems of care, (2) risk stratification, (3) education, (4) optimization of pharmacotherapy, and (5) cost/affordability. While ACS guidelines clearly represent a valuable standard of care, the group concluded that these challenges can be best met by establishing cardiac networks and individual hospital models/clinical pathways taking into account local risk factors (including socioeconomic status), affordability and availability of pharmacotherapies/invasive facilities, and the nature of local healthcare systems. Potential solutions central to the optimization of ACS medical management in the APAC region are outlined with specific recommendations. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Healthy Chilean Adolescents with HOMA-IR ≥ 2.6 Have Increased Cardiometabolic Risk: Association with Genetic, Biological, and Environmental Factors

PubMed Central

Burrows, R.; Correa-Burrows, P.; Reyes, M.; Blanco, E.; Albala, C.; Gahagan, S.

2015-01-01

Objective. To determine the optimal cutoff of the homeostasis model assessment-insulin resistance (HOMA-IR) for diagnosis of the metabolic syndrome (MetS) in adolescents and examine whether insulin resistance (IR), determined by this method, was related to genetic, biological, and environmental factors. Methods. In 667 adolescents (16.8 ± 0.3 y), BMI, waist circumference, glucose, insulin, adiponectin, diet, and physical activity were measured. Fat and fat-free mass were assessed by dual-energy X-ray absorptiometry. Family history of type 2 diabetes (FHDM) was reported. We determined the optimal cutoff of HOMA-IR to diagnose MetS (IDF criteria) using ROC analysis. IR was defined as HOMA-IR values above the cutoff. We tested the influence of genetic, biological, and environmental factors on IR using logistic regression analyses. Results. Of the participants, 16% were obese and 9.4 % met criteria for MetS. The optimal cutoff for MetS diagnosis was a HOMA-IR value of 2.6. Based on this value, 16.3% of participants had IR. Adolescents with IR had a significantly higher prevalence of obesity, abdominal obesity, fasting hyperglycemia, and MetS compared to those who were not IR. FHDM, sarcopenia, obesity, and low adiponectin significantly increased the risk of IR. Conclusions. In adolescents, HOMA-IR ≥ 2.6 was associated with greater cardiometabolic risk. PMID:26273675

Healthy Chilean Adolescents with HOMA-IR ≥ 2.6 Have Increased Cardiometabolic Risk: Association with Genetic, Biological, and Environmental Factors.

PubMed

Burrows, R; Correa-Burrows, P; Reyes, M; Blanco, E; Albala, C; Gahagan, S

2015-01-01

To determine the optimal cutoff of the homeostasis model assessment-insulin resistance (HOMA-IR) for diagnosis of the metabolic syndrome (MetS) in adolescents and examine whether insulin resistance (IR), determined by this method, was related to genetic, biological, and environmental factors. In 667 adolescents (16.8 ± 0.3 y), BMI, waist circumference, glucose, insulin, adiponectin, diet, and physical activity were measured. Fat and fat-free mass were assessed by dual-energy X-ray absorptiometry. Family history of type 2 diabetes (FHDM) was reported. We determined the optimal cutoff of HOMA-IR to diagnose MetS (IDF criteria) using ROC analysis. IR was defined as HOMA-IR values above the cutoff. We tested the influence of genetic, biological, and environmental factors on IR using logistic regression analyses. Of the participants, 16% were obese and 9.4 % met criteria for MetS. The optimal cutoff for MetS diagnosis was a HOMA-IR value of 2.6. Based on this value, 16.3% of participants had IR. Adolescents with IR had a significantly higher prevalence of obesity, abdominal obesity, fasting hyperglycemia, and MetS compared to those who were not IR. FHDM, sarcopenia, obesity, and low adiponectin significantly increased the risk of IR. In adolescents, HOMA-IR ≥ 2.6 was associated with greater cardiometabolic risk.

Replica analysis for the duality of the portfolio optimization problem

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Replica analysis for the duality of the portfolio optimization problem.

PubMed

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Integrating geological uncertainty in long-term open pit mine production planning by ant colony optimization

NASA Astrophysics Data System (ADS)

Gilani, Seyed-Omid; Sattarvand, Javad

2016-02-01

Meeting production targets in terms of ore quantity and quality is critical for a successful mining operation. In-situ grade uncertainty causes both deviations from production targets and general financial deficits. A new stochastic optimization algorithm based on ant colony optimization (ACO) approach is developed herein to integrate geological uncertainty described through a series of the simulated ore bodies. Two different strategies were developed based on a single predefined probability value (Prob) and multiple probability values (Pro bnt) , respectively in order to improve the initial solutions that created by deterministic ACO procedure. Application at the Sungun copper mine in the northwest of Iran demonstrate the abilities of the stochastic approach to create a single schedule and control the risk of deviating from production targets over time and also increase the project value. A comparison between two strategies and traditional approach illustrates that the multiple probability strategy is able to produce better schedules, however, the single predefined probability is more practical in projects requiring of high flexibility degree.

A Bayesian-based two-stage inexact optimization method for supporting stream water quality management in the Three Gorges Reservoir region.

PubMed

Hu, X H; Li, Y P; Huang, G H; Zhuang, X W; Ding, X W

2016-05-01

In this study, a Bayesian-based two-stage inexact optimization (BTIO) method is developed for supporting water quality management through coupling Bayesian analysis with interval two-stage stochastic programming (ITSP). The BTIO method is capable of addressing uncertainties caused by insufficient inputs in water quality model as well as uncertainties expressed as probabilistic distributions and interval numbers. The BTIO method is applied to a real case of water quality management for the Xiangxi River basin in the Three Gorges Reservoir region to seek optimal water quality management schemes under various uncertainties. Interval solutions for production patterns under a range of probabilistic water quality constraints have been generated. Results obtained demonstrate compromises between the system benefit and the system failure risk due to inherent uncertainties that exist in various system components. Moreover, information about pollutant emission is accomplished, which would help managers to adjust production patterns of regional industry and local policies considering interactions of water quality requirement, economic benefit, and industry structure.

Rise and Shock: Optimal Defibrillator Placement in a High-rise Building.

PubMed

Chan, Timothy C Y

2017-01-01

Out-of-hospital cardiac arrests (OHCA) in high-rise buildings experience lower survival and longer delays until paramedic arrival. Use of publicly accessible automated external defibrillators (AED) can improve survival, but "vertical" placement has not been studied. We aim to determine whether elevator-based or lobby-based AED placement results in shorter vertical distance travelled ("response distance") to OHCAs in a high-rise building. We developed a model of a single-elevator, n-floor high-rise building. We calculated and compared the average distance from AED to floor of arrest for the two AED locations. We modeled OHCA occurrences using floor-specific Poisson processes, the risk of OHCA on the ground floor (λ 1 ) and the risk on any above-ground floor (λ). The elevator was modeled with an override function enabling direct travel to the target floor. The elevator location upon override was modeled as a discrete uniform random variable. Calculations used the laws of probability. Elevator-based AED placement had shorter average response distance if the number of floors (n) in the building exceeded three quarters of the ratio of ground-floor OHCA risk to above-ground floor risk (λ 1 /λ) plus one half (n ≥ 3λ 1 /4λ + 0.5). Otherwise, a lobby-based AED had shorter average response distance. If OHCA risk on each floor was equal, an elevator-based AED had shorter average response distance. Elevator-based AEDs travel less vertical distance to OHCAs in tall buildings or those with uniform vertical risk, while lobby-based AEDs travel less vertical distance in buildings with substantial lobby, underground, and nearby street-level traffic and OHCA risk.

Biological-based and physical-based optimization for biological evaluation of prostate patient's plans

NASA Astrophysics Data System (ADS)

Sukhikh, E.; Sheino, I.; Vertinsky, A.

2017-09-01

Modern modalities of radiation treatment therapy allow irradiation of the tumor to high dose values and irradiation of organs at risk (OARs) to low dose values at the same time. In this paper we study optimal radiation treatment plans made in Monaco system. The first aim of this study was to evaluate dosimetric features of Monaco treatment planning system using biological versus dose-based cost functions for the OARs and irradiation targets (namely tumors) when the full potential of built-in biological cost functions is utilized. The second aim was to develop criteria for the evaluation of radiation dosimetry plans for patients based on the macroscopic radiobiological criteria - TCP/NTCP. In the framework of the study four dosimetric plans were created utilizing the full extent of biological and physical cost functions using dose calculation-based treatment planning for IMRT Step-and-Shoot delivery of stereotactic body radiation therapy (SBRT) in prostate case (5 fractions per 7 Gy).

A Longitudinal Examination of Hope and Optimism and Their Role in Type 1 Diabetes in Youths

PubMed Central

Steele, Ric G.; Nelson, Michael B.; Peugh, James; Egan, Anna; Clements, Mark; Patton, Susana R.

2016-01-01

Objectives To test the longitudinal associations between hope and optimism and health outcomes (i.e., HbA1c and self-monitored blood glucose [SMBG]) among youths with Type 1 diabetes mellitus (T1DM) over a 6-month period. Methods A total of 110 participants (aged 10–16 years) completed study measures at Time 1, and 81 completed measures at Time 2. Analyses examined hope and optimism as predictors of change in health outcomes, and examined SMBG as a mediator of the relationship between hope and optimism, and HbA1c. Results Change in hope, but not optimism, was associated with change in SMBG and HbA1c. Change in SMBG mediated the relationship between change in hope and HbA1c, but not between optimism and HbA1c. Conclusions It may be beneficial to assess hope in pediatric T1DM patients to identify youths who may be at risk for poor diabetes management, and to test the benefit of hope-based intervention efforts in clinical studies. PMID:26628250

An optimization tool for satellite equipment layout

NASA Astrophysics Data System (ADS)

Qin, Zheng; Liang, Yan-gang; Zhou, Jian-ping

2018-01-01

Selection of the satellite equipment layout with performance constraints is a complex task which can be viewed as a constrained multi-objective optimization and a multiple criteria decision making problem. The layout design of a satellite cabin involves the process of locating the required equipment in a limited space, thereby satisfying various behavioral constraints of the interior and exterior environments. The layout optimization of satellite cabin in this paper includes the C.G. offset, the moments of inertia and the space debris impact risk of the system, of which the impact risk index is developed to quantify the risk to a satellite cabin of coming into contact with space debris. In this paper an optimization tool for the integration of CAD software as well as the optimization algorithms is presented, which is developed to automatically find solutions for a three-dimensional layout of equipment in satellite. The effectiveness of the tool is also demonstrated by applying to the layout optimization of a satellite platform.

Optimal allocation of conservation effort among subpopulations of a threatened species: how important is patch quality?

PubMed

Chauvenet, Aliénor L M; Baxter, Peter W J; McDonald-Madden, Eve; Possingham, Hugh P

2010-04-01

Money is often a limiting factor in conservation, and attempting to conserve endangered species can be costly. Consequently, a framework for optimizing fiscally constrained conservation decisions for a single species is needed. In this paper we find the optimal budget allocation among isolated subpopulations of a threatened species to minimize local extinction probability. We solve the problem using stochastic dynamic programming, derive a useful and simple alternative guideline for allocating funds, and test its performance using forward simulation. The model considers subpopulations that persist in habitat patches of differing quality, which in our model is reflected in different relationships between money invested and extinction risk. We discover that, in most cases, subpopulations that are less efficient to manage should receive more money than those that are more efficient to manage, due to higher investment needed to reduce extinction risk. Our simple investment guideline performs almost as well as the exact optimal strategy. We illustrate our approach with a case study of the management of the Sumatran tiger, Panthera tigris sumatrae, in Kerinci Seblat National Park (KSNP), Indonesia. We find that different budgets should be allocated to the separate tiger subpopulations in KSNP. The subpopulation that is not at risk of extinction does not require any management investment. Based on the combination of risks of extinction and habitat quality, the optimal allocation for these particular tiger subpopulations is an unusual case: subpopulations that occur in higher-quality habitat (more efficient to manage) should receive more funds than the remaining subpopulation that is in lower-quality habitat. Because the yearly budget allocated to the KSNP for tiger conservation is small, to guarantee the persistence of all the subpopulations that are currently under threat we need to prioritize those that are easier to save. When allocating resources among subpopulations of a threatened species, the combined effects of differences in habitat quality, cost of action, and current subpopulation probability of extinction need to be integrated. We provide a useful guideline for allocating resources among isolated subpopulations of any threatened species.

Optimizing colorectal cancer screening by race and sex: Microsimulation analysis II to inform the American Cancer Society colorectal cancer screening guideline.

PubMed

Meester, Reinier G S; Peterse, Elisabeth F P; Knudsen, Amy B; de Weerdt, Anne C; Chen, Jennifer C; Lietz, Anna P; Dwyer, Andrea; Ahnen, Dennis J; Siegel, Rebecca L; Smith, Robert A; Zauber, Ann G; Lansdorp-Vogelaar, Iris

2018-05-30

Colorectal cancer (CRC) risk varies by race and sex. This study, 1 of 2 microsimulation analyses to inform the 2018 American Cancer Society CRC screening guideline, explored the influence of race and sex on optimal CRC screening strategies. Two Cancer Intervention and Surveillance Modeling Network microsimulation models, informed by US incidence data, were used to evaluate a variety of screening methods, ages to start and stop, and intervals for 4 demographic subgroups (black and white males and females) under 2 scenarios for the projected lifetime CRC risk for 40-year-olds: 1) assuming that risk had remained stable since the early screening era and 2) assuming that risk had increased proportionally to observed incidence trends under the age of 40 years. Model-based screening recommendations were based on the predicted level of benefit (life-years gained) and burden (required number of colonoscopies), the incremental burden-to-benefit ratio, and the relative efficiency in comparison with strategies with similar burdens. When lifetime CRC risk was assumed to be stable over time, the models differed in the recommended age to start screening for whites (45 vs 50 years) but consistently recommended screening from the age of 45 years for blacks. When CRC risk was assumed to be increased, the models recommended starting at the age of 45 years, regardless of race and sex. Strategies recommended under both scenarios included colonoscopy every 10 or 15 years, annual fecal immunochemical testing, and computed tomographic colonography every 5 years through the age of 75 years. Microsimulation modeling suggests that CRC screening should be considered from the age of 45 years for blacks and for whites if the lifetime risk has increased proportionally to the incidence for younger adults. Cancer 2018. © 2018 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. © 2018 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

A Decision Support Model and Tool to Assist Financial Decision-Making in Universities

ERIC Educational Resources Information Center

Bhayat, Imtiaz; Manuguerra, Maurizio; Baldock, Clive

2015-01-01

In this paper, a model and tool is proposed to assist universities and other mission-based organisations to ascertain systematically the optimal portfolio of projects, in any year, meeting the organisations risk tolerances and available funds. The model and tool presented build on previous work on university operations and decision support systems…

The management of women at high risk for the development of breast cancer: risk estimation and preventative strategies.

PubMed

Sakorafas, George H

2003-04-01

Despite recent progress in the diagnostic and therapeutic approaches to the management of women with breast cancer, at least one third of these women will ultimately die from their disease. This resulted in a new focus on breast cancer prevention, especially for the woman designed as "high-risk". The continuing challenge is to identify reliable markers to accurately recognize this group of women, who are more likely to develop breast cancer. This will allow a targeted specific counseling and the application of preventative measures. Management options in high-risk women include intensive cancer surveillance, chemoprevention (mainly using tamoxifen), and prophylactic surgery (preferentially total mastectomy). Cancer surveillance is the most preferred management option. Currently, no data exists comparing prophylactic mastectomy vs. surveillance vs. chemoprevention. Thus, despite significant advances in our understanding of the biology of breast cancer, many questions remain unanswered concerning the optimal management of the high-risk woman. Patient counseling has a central role in the decision-making process and should be based on a multidisciplinary approach. The individual woman will make the final decision based on the amount of risk she is willing to accept. It is hoped that other preventative methods, such as gene therapy based on an accurate identification of specific genetic changes, will be developed in the future.

Patient-specific radiation dose and cancer risk estimation in pediatric chest CT: a study in 30 patients

NASA Astrophysics Data System (ADS)

Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

2010-04-01

Radiation-dose awareness and optimization in CT can greatly benefit from a dosereporting system that provides radiation dose and cancer risk estimates specific to each patient and each CT examination. Recently, we reported a method for estimating patientspecific dose from pediatric chest CT. The purpose of this study is to extend that effort to patient-specific risk estimation and to a population of pediatric CT patients. Our study included thirty pediatric CT patients (16 males and 14 females; 0-16 years old), for whom full-body computer models were recently created based on the patients' clinical CT data. Using a validated Monte Carlo program, organ dose received by the thirty patients from a chest scan protocol (LightSpeed VCT, 120 kVp, 1.375 pitch, 40-mm collimation, pediatric body scan field-of-view) was simulated and used to estimate patient-specific effective dose. Risks of cancer incidence were calculated for radiosensitive organs using gender-, age-, and tissue-specific risk coefficients and were used to derive patientspecific effective risk. The thirty patients had normalized effective dose of 3.7-10.4 mSv/100 mAs and normalized effective risk of 0.5-5.8 cases/1000 exposed persons/100 mAs. Normalized lung dose and risk of lung cancer correlated strongly with average chest diameter (correlation coefficient: r = -0.98 to -0.99). Normalized effective risk also correlated strongly with average chest diameter (r = -0.97 to -0.98). These strong correlations can be used to estimate patient-specific dose and risk prior to or after an imaging study to potentially guide healthcare providers in justifying CT examinations and to guide individualized protocol design and optimization.

Inconsistent Investment and Consumption Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kronborg, Morten Tolver, E-mail: mtk@atp.dk; Steffensen, Mogens, E-mail: mogens@math.ku.dk

In a traditional Black–Scholes market we develop a verification theorem for a general class of investment and consumption problems where the standard dynamic programming principle does not hold. The theorem is an extension of the standard Hamilton–Jacobi–Bellman equation in the form of a system of non-linear differential equations. We derive the optimal investment and consumption strategy for a mean-variance investor without pre-commitment endowed with labor income. In the case of constant risk aversion it turns out that the optimal amount of money to invest in stocks is independent of wealth. The optimal consumption strategy is given as a deterministic bang-bangmore » strategy. In order to have a more realistic model we allow the risk aversion to be time and state dependent. Of special interest is the case were the risk aversion is inversely proportional to present wealth plus the financial value of future labor income net of consumption. Using the verification theorem we give a detailed analysis of this problem. It turns out that the optimal amount of money to invest in stocks is given by a linear function of wealth plus the financial value of future labor income net of consumption. The optimal consumption strategy is again given as a deterministic bang-bang strategy. We also calculate, for a general time and state dependent risk aversion function, the optimal investment and consumption strategy for a mean-standard deviation investor without pre-commitment. In that case, it turns out that it is optimal to take no risk at all.« less

Electric vehicle (EV) storage supply chain risk and the energy market: A micro and macroeconomic risk management approach

NASA Astrophysics Data System (ADS)

Aguilar, Susanna D.

As a cost effective storage technology for renewable energy sources, Electric Vehicles can be integrated into energy grids. Integration must be optimized to ascertain that renewable energy is available through storage when demand exists so that cost of electricity is minimized. Optimization models can address economic risks associated with the EV supply chain- particularly the volatility in availability and cost of critical materials used in the manufacturing of EV motors and batteries. Supply chain risk can reflect itself in a shortage of storage, which can increase the price of electricity. We propose a micro-and macroeconomic framework for managing supply chain risk through utilization of a cost optimization model in combination with risk management strategies at the microeconomic and macroeconomic level. The study demonstrates how risk from the EVs vehicle critical material supply chain affects manufacturers, smart grid performance, and energy markets qualitatively and quantitatively. Our results illustrate how risk in the EV supply chain affects EV availability and the cost of ancillary services, and how EV critical material supply chain risk can be mitigated through managerial strategies and policy.

Enhanced index tracking modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin

2013-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Using Mobile Phone Data to Predict the Spatial Spread of Cholera

PubMed Central

Bengtsson, Linus; Gaudart, Jean; Lu, Xin; Moore, Sandra; Wetter, Erik; Sallah, Kankoe; Rebaudet, Stanislas; Piarroux, Renaud

2015-01-01

Effective response to infectious disease epidemics requires focused control measures in areas predicted to be at high risk of new outbreaks. We aimed to test whether mobile operator data could predict the early spatial evolution of the 2010 Haiti cholera epidemic. Daily case data were analysed for 78 study areas from October 16 to December 16, 2010. Movements of 2.9 million anonymous mobile phone SIM cards were used to create a national mobility network. Two gravity models of population mobility were implemented for comparison. Both were optimized based on the complete retrospective epidemic data, available only after the end of the epidemic spread. Risk of an area experiencing an outbreak within seven days showed strong dose-response relationship with the mobile phone-based infectious pressure estimates. The mobile phone-based model performed better (AUC 0.79) than the retrospectively optimized gravity models (AUC 0.66 and 0.74, respectively). Infectious pressure at outbreak onset was significantly correlated with reported cholera cases during the first ten days of the epidemic (p < 0.05). Mobile operator data is a highly promising data source for improving preparedness and response efforts during cholera outbreaks. Findings may be particularly important for containment efforts of emerging infectious diseases, including high-mortality influenza strains. PMID:25747871

Using mobile phone data to predict the spatial spread of cholera.

PubMed

Bengtsson, Linus; Gaudart, Jean; Lu, Xin; Moore, Sandra; Wetter, Erik; Sallah, Kankoe; Rebaudet, Stanislas; Piarroux, Renaud

2015-03-09

Effective response to infectious disease epidemics requires focused control measures in areas predicted to be at high risk of new outbreaks. We aimed to test whether mobile operator data could predict the early spatial evolution of the 2010 Haiti cholera epidemic. Daily case data were analysed for 78 study areas from October 16 to December 16, 2010. Movements of 2.9 million anonymous mobile phone SIM cards were used to create a national mobility network. Two gravity models of population mobility were implemented for comparison. Both were optimized based on the complete retrospective epidemic data, available only after the end of the epidemic spread. Risk of an area experiencing an outbreak within seven days showed strong dose-response relationship with the mobile phone-based infectious pressure estimates. The mobile phone-based model performed better (AUC 0.79) than the retrospectively optimized gravity models (AUC 0.66 and 0.74, respectively). Infectious pressure at outbreak onset was significantly correlated with reported cholera cases during the first ten days of the epidemic (p < 0.05). Mobile operator data is a highly promising data source for improving preparedness and response efforts during cholera outbreaks. Findings may be particularly important for containment efforts of emerging infectious diseases, including high-mortality influenza strains.

Evidence-based exercise prescription for balance and falls prevention: a current review of the literature.

PubMed

Shubert, Tiffany E

2011-01-01

Falls are the leading cause of emergency department visits, hospital admissions, and unintentional death for older adults. Balance and strength impairments are common falls risk factors for community-dwelling older adults. Though physical therapists commonly treat balance and strength, standardized falls screening has not been fully incorporated into physical therapy practice and there is much variation in the frequency, intensity, and duration of therapy prescribed to achieve optimal results. For community-dwelling older adults, a progressive exercise program that focuses on moderate to high-intensity balance exercises appears to be one of the most effective interventions to prevent falls. For more frail older adults in institutional settings, exercise programs in addition to multifactorial interventions appear to show promise as effective falls prevention interventions. The minimum dose of exercise to protect an older adult against falls is 50 hours. This article describes the current best practices for physical therapists to effectively improve balance and manage falls risk in patients. The unique challenges and opportunities for physical therapists to incorporate evidence-based fall-prevention strategies are discussed. Innovative practice models incorporating evidence-based fall-prevention programs and partnerships with public health and aging service providers to create a continuum of care and achieve the optimal dose of balance training are presented.

Interbody fusion cage design using integrated global layout and local microstructure topology optimization.

PubMed

Lin, Chia-Ying; Hsiao, Chun-Ching; Chen, Po-Quan; Hollister, Scott J

2004-08-15

An approach combining global layout and local microstructure topology optimization was used to create a new interbody fusion cage design that concurrently enhanced stability, biofactor delivery, and mechanical tissue stimulation for improved arthrodesis. To develop a new interbody fusion cage design by topology optimization with porous internal architecture. To compare the performance of this new design to conventional threaded cage designs regarding early stability and long-term stress shielding effects on ingrown bone. Conventional interbody cage designs mainly fall into categories of cylindrical or rectangular shell shapes. The designs contribute to rigid stability and maintain disc height for successful arthrodesis but may also suffer mechanically mediated failures of dislocation or subsidence, as well as the possibility of bone resorption. The new optimization approach created a cage having designed microstructure that achieved desired mechanical performance while providing interconnected channels for biofactor delivery. The topology optimization algorithm determines the material layout under desirable volume fraction (50%) and displacement constraints favorable to bone formation. A local microstructural topology optimization method was used to generate periodic microstructures for porous isotropic materials. Final topology was generated by the integration of the two-scaled structures according to segmented regions and the corresponding material density. Image-base finite element analysis was used to compare the mechanical performance of the topology-optimized cage and conventional threaded cage. The final design can be fabricated by a variety of Solid Free-Form systems directly from the image output. The new design exhibited a narrower, more uniform displacement range than the threaded cage design and lower stress at the cage-vertebra interface, suggesting a reduced risk of subsidence. Strain energy density analysis also indicated that a higher portion of total strain energy density was transferred into the new bone region inside the new designed cage, indicating a reduced risk of stress shielding. The new design approach using integrated topology optimization demonstrated comparable or better stability by limited displacement and reduced localized deformation related to the risk of subsidence. Less shielding of newly formed bone was predicted inside the new designed cage. Using the present approach, it is also possible to tailor cage design for specific materials, either titanium or polymer, that can attain the desired balance between stability, reduced stress shielding, and porosity for biofactor delivery.

Translating research into practice: is evidence-based medicine being practiced in military-relevant orthopedic trauma?

PubMed

Niles, Sarah E; Balazs, George C; Cawley, Christina; Bosse, Michael; Mackenzie, Ellen; Li, Yaunzhang; Andersen, Romney C

2015-04-01

Orthopedic trauma remains one of the most survivable battlefield injuries seen in modern conflicts. Translating research into practice is a critical bridge that permits surgeons to further optimize medical outcomes. Orthopedic surgeons serving in the military may treat little to no trauma in their stateside practice. In conflict zones, however, the majority of their patients will have traumatic injuries. Determining risk factors for nonevidence-based practice can help identify provider knowledge gaps, which can then be targeted before deployment. Surveys were developed which sought to identify factors contributing to continued medical education and practice, as well as scenario-based questions on military-relevant orthopedic trauma. Analysis of 188 survey respondents revealed that providers with military service and less than 10 years of practice are optimally bridging research into military-relevant orthopedic trauma practice. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

A Fast Method for Embattling Optimization of Ground-Based Radar Surveillance Network

NASA Astrophysics Data System (ADS)

Jiang, H.; Cheng, H.; Zhang, Y.; Liu, J.

A growing number of space activities have created an orbital debris environment that poses increasing impact risks to existing space systems and human space flight. For the safety of in-orbit spacecraft, a lot of observation facilities are needed to catalog space objects, especially in low earth orbit. Surveillance of Low earth orbit objects are mainly rely on ground-based radar, due to the ability limitation of exist radar facilities, a large number of ground-based radar need to build in the next few years in order to meet the current space surveillance demands. How to optimize the embattling of ground-based radar surveillance network is a problem to need to be solved. The traditional method for embattling optimization of ground-based radar surveillance network is mainly through to the detection simulation of all possible stations with cataloged data, and makes a comprehensive comparative analysis of various simulation results with the combinational method, and then selects an optimal result as station layout scheme. This method is time consuming for single simulation and high computational complexity for the combinational analysis, when the number of stations increases, the complexity of optimization problem will be increased exponentially, and cannot be solved with traditional method. There is no better way to solve this problem till now. In this paper, target detection procedure was simplified. Firstly, the space coverage of ground-based radar was simplified, a space coverage projection model of radar facilities in different orbit altitudes was built; then a simplified objects cross the radar coverage model was established according to the characteristics of space objects orbit motion; after two steps simplification, the computational complexity of the target detection was greatly simplified, and simulation results shown the correctness of the simplified results. In addition, the detection areas of ground-based radar network can be easily computed with the simplified model, and then optimized the embattling of ground-based radar surveillance network with the artificial intelligent algorithm, which can greatly simplifies the computational complexities. Comparing with the traditional method, the proposed method greatly improved the computational efficiency.

Hemodynamic and oxygen transport patterns for outcome prediction, therapeutic goals, and clinical algorithms to improve outcome. Feasibility of artificial intelligence to customize algorithms.

PubMed

Shoemaker, W C; Patil, R; Appel, P L; Kram, H B

1992-11-01

A generalized decision tree or clinical algorithm for treatment of high-risk elective surgical patients was developed from a physiologic model based on empirical data. First, a large data bank was used to do the following: (1) describe temporal hemodynamic and oxygen transport patterns that interrelate cardiac, pulmonary, and tissue perfusion functions in survivors and nonsurvivors; (2) define optimal therapeutic goals based on the supranormal oxygen transport values of high-risk postoperative survivors; (3) compare the relative effectiveness of alternative therapies in a wide variety of clinical and physiologic conditions; and (4) to develop criteria for titration of therapy to the endpoints of the supranormal optimal goals using cardiac index (CI), oxygen delivery (DO2), and oxygen consumption (VO2) as proxy outcome measures. Second, a general purpose algorithm was generated from these data and tested in preoperatively randomized clinical trials of high-risk surgical patients. Improved outcome was demonstrated with this generalized algorithm. The concept that the supranormal values represent compensations that have survival value has been corroborated by several other groups. We now propose a unique approach to refine the generalized algorithm to develop customized algorithms and individualized decision analysis for each patient's unique problems. The present article describes a preliminary evaluation of the feasibility of artificial intelligence techniques to accomplish individualized algorithms that may further improve patient care and outcome.

Affective state influences perception by affecting decision parameters underlying bias and sensitivity.

PubMed

Lynn, Spencer K; Zhang, Xuan; Barrett, Lisa Feldman

2012-08-01

Studies of the effect of affect on perception often show consistent directional effects of a person's affective state on perception. Unpleasant emotions have been associated with a "locally focused" style of stimulus evaluation, and positive emotions with a "globally focused" style. Typically, however, studies of affect and perception have not been conducted under the conditions of perceptual uncertainty and behavioral risk inherent to perceptual judgments outside the laboratory. We investigated the influence of perceivers' experienced affect (valence and arousal) on the utility of social threat perception by combining signal detection theory and behavioral economics. We compared 3 perceptual decision environments that systematically differed with respect to factors that underlie uncertainty and risk: the base rate of threat, the costs of incorrect identification threat, and the perceptual similarity of threats and nonthreats. We found that no single affective state yielded the best performance on the threat perception task across the 3 environments. Unpleasant valence promoted calibration of response bias to base rate and costs, high arousal promoted calibration of perceptual sensitivity to perceptual similarity, and low arousal was associated with an optimal adjustment of bias to sensitivity. However, the strength of these associations was conditional upon the difficulty of attaining optimal bias and high sensitivity, such that the effect of the perceiver's affective state on perception differed with the cause and/or level of uncertainty and risk.

Affective State Influences Perception by Affecting Decision Parameters Underlying Bias and Sensitivity

PubMed Central

Lynn, Spencer K.; Zhang, Xuan; Barrett, Lisa Feldman

2012-01-01

Studies of the effect of affect on perception often show consistent directional effects of a person’s affective state on perception. Unpleasant emotions have been associated with a “locally focused” style of stimulus evaluation, and positive emotions with a “globally focused” style. Typically, however, studies of affect and perception have not been conducted under the conditions of perceptual uncertainty and behavioral risk inherent to perceptual judgments outside the laboratory. We investigated the influence of perceivers’ experience affect (valence and arousal) on the utility of social threat perception by combining signal detection theory and behavioral economics. We created three perceptual decision environments that systematically differed with respect to factors that underlie uncertainty and risk: the base rate of threat, the costs of incorrect identification threat, and the perceptual similarity of threats and non-threats. We found that no single affective state yielded the best performance on the threat perception task across the three environments. Unpleasant valence promoted calibration of response bias to base rate and costs, high arousal promoted calibration of perceptual sensitivity to perceptual similarity, and low arousal was associated with an optimal adjustment of bias to sensitivity. However, the strength of these associations was conditional upon the difficulty of attaining optimal bias and high sensitivity, such that the effect of the perceiver’s affective state on perception differed with the cause and/or level of uncertainty and risk. PMID:22251054

Optimization-based decision support to assist in logistics planning for hospital evacuations.

PubMed

Glick, Roger; Bish, Douglas R; Agca, Esra

2013-01-01

The evacuation of the hospital is a very complex process and evacuation planning is an important part of a hospital's emergency management plan. There are numerous factors that affect the evacuation plan including the nature of threat, availability of resources and staff the characteristics of the evacuee population, and risk to patients and staff. The safety and health of patients is of fundamental importance, but safely moving patients to alternative care facilities while under threat is a very challenging task. This article describes the logistical issues and complexities involved in planning and execution of hospital evacuations. Furthermore, this article provides examples of how optimization-based decision support tools can help evacuation planners to better plan for complex evacuations by providing real-world solutions to various evacuation scenarios.

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions

PubMed Central

2018-01-01

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence. PMID:29543711

A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines

PubMed Central

Jenssen, Robert; Kloft, Marius; Zien, Alexander; Sonnenburg, Sören; Müller, Klaus-Robert

2012-01-01

We provide a novel interpretation of the dual of support vector machines (SVMs) in terms of scatter with respect to class prototypes and their mean. As a key contribution, we extend this framework to multiple classes, providing a new joint Scatter SVM algorithm, at the level of its binary counterpart in the number of optimization variables. This enables us to implement computationally efficient solvers based on sequential minimal and chunking optimization. As a further contribution, the primal problem formulation is developed in terms of regularized risk minimization and the hinge loss, revealing the score function to be used in the actual classification of test patterns. We investigate Scatter SVM properties related to generalization ability, computational efficiency, sparsity and sensitivity maps, and report promising results. PMID:23118845

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions.

PubMed

Alva, Maria L

2018-03-15

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence.

Optimal duration of dual anti-platelet therapy after percutaneous coronary intervention: 2016 consensus position of the Italian Society of Cardiology.

PubMed

Barillà, Francesco; Pelliccia, Francesco; Borzi, Mauro; Camici, Paolo; Cas, Livio Dei; Di Biase, Matteo; Indolfi, Ciro; Mercuro, Giuseppe; Montemurro, Vincenzo; Padeletti, Luigi; Filardi, Pasquale Perrone; Vizza, Carmine D; Romeo, Francesco

2017-01-01

Definition of the optimal duration of dual anti-platelet therapy (DAPT) is an important clinical issue, given the large number of patients having percutaneous coronary intervention (PCI), the costs and risks of pharmacologic therapy, the consequences of stent thrombosis, and the potential benefits of DAPT in preventing ischaemic outcomes beyond stent thrombosis. Nowadays, the rationale for a prolonged duration of DAPT should be not only the prevention of stent thrombosis, but also the prevention of ischaemic events unrelated to the coronary stenosis treated with index PCI. A higher predisposition to athero-thrombosis may persist for years after an acute myocardial infarction, and even stable patients with a history of prior myocardial infarction are at high risk for major adverse cardiovascular events. Recently, results of pre-specified post-hoc analyses of randomized clinical trials, including the PEGASUS-TIMI 54 trial, have shed light on strategies of DAPT in various clinical situations, and should impact the next rounds of international guidelines, and also routine practice. Accordingly, the 2015 to 2016 the Board of the Italian Society of Cardiology addressed newer recommendations on duration of DAPT based on most recent scientific information. The document states that physicians should decide duration of DAPT on an individual basis, taking into account ischaemic and bleeding risks of any given patient. Indeed, current controversy surrounding optimal duration of DAPT clearly reflects the fact that, nowadays, a one size fits all strategy cannot be reliably applied to patients treated with PCI. Indeed, patients usually have factors for both increased ischaemic and bleeding risks that must be carefully evaluated to assess the benefit/risk ratio of prolonged DAPT. Personalized management of DAPT must be seen as a dynamic prescription with regular re-evaluations of the risk/benefit to the patient according to changes in his/her clinical profile. Also, in order to derive more benefit than harm from new treatments, a multi-parametric approach using several risk scores of the ischaemic and bleeding risks might improve the process of risk factor characterization. In patients with high ischaemic risk, particularly those with a history of myocardial infarction, the benefits of extended DAPT (particularly with ticagrelor up to 3 years) are likely to outweigh the risks.

Impact of electronic health record-based, pharmacist-driven valganciclovir dose optimization in solid organ transplant recipients.

PubMed

Hensler, David; Richardson, Chad L; Brown, Joslyn; Tseng, Christine; DeCamp, Phyllis J; Yang, Amy; Pawlowski, Anna; Ho, Bing; Ison, Michael G

2018-04-01

Prophylaxis with valganciclovir reduces the incidence of cytomegalovirus (CMV) infection following solid organ transplant (SOT). Under-dosing of valganciclovir is associated with an increased risk of CMV infection and development of ganciclovir-resistant CMV. An automated electronic health record (EHR)-based, pharmacist-driven program was developed to optimize dosing of valganciclovir in solid organ transplant recipients at a large transplant center. Two cohorts of kidney, pancreas-kidney, and liver transplant recipients from our center pre-implementation (April 2011-March 2012, n = 303) and post-implementation of the optimization program (September 2012-August 2013, n=263) had demographic and key outcomes data collected for 1 year post-transplant. The 1-year incidence of CMV infection dropped from 56 (18.5%) to 32 (12.2%, P = .05) and the incidence of breakthrough infections on prophylaxis was cut in half (61% vs 34%, P = .03) after implementation of the dose optimization program. The hazard ratio of developing CMV was 1.64 (95% CI 1.06-2.60, P = .027) for the pre-implementation group after adjusting for potential confounders. The program also resulted in a numerical reduction in the number of ganciclovir-resistant CMV cases (2 [0.7%] pre-implementation vs 0 post-implementation). An EHR-based, pharmacist-driven valganciclovir dose optimization program was associated with reduction in CMV infections. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Optimized knock-in of point mutations in zebrafish using CRISPR/Cas9.

PubMed

Prykhozhij, Sergey V; Fuller, Charlotte; Steele, Shelby L; Veinotte, Chansey J; Razaghi, Babak; Robitaille, Johane M; McMaster, Christopher R; Shlien, Adam; Malkin, David; Berman, Jason N

2018-06-14

We have optimized point mutation knock-ins into zebrafish genomic sites using clustered regularly interspaced palindromic repeats (CRISPR)/Cas9 reagents and single-stranded oligodeoxynucleotides. The efficiency of knock-ins was assessed by a novel application of allele-specific polymerase chain reaction and confirmed by high-throughput sequencing. Anti-sense asymmetric oligo design was found to be the most successful optimization strategy. However, cut site proximity to the mutation and phosphorothioate oligo modifications also greatly improved knock-in efficiency. A previously unrecognized risk of off-target trans knock-ins was identified that we obviated through the development of a workflow for correct knock-in detection. Together these strategies greatly facilitate the study of human genetic diseases in zebrafish, with additional applicability to enhance CRISPR-based approaches in other animal model systems.

Temporal variation of optimal UV exposure time over Korea: risks and benefits of surface UV radiation

NASA Astrophysics Data System (ADS)

Lee, Y. G.; Koo, J. H.

2015-12-01

Solar UV radiation in a wavelength range between 280 to 400 nm has both positive and negative influences on human body. Surface UV radiation is the main natural source of vitamin D, providing the promotion of bone and musculoskeletal health and reducing the risk of a number of cancers and other medical conditions. However, overexposure to surface UV radiation is significantly related with the majority of skin cancer, in addition other negative health effects such as sunburn, skin aging, and some forms of eye cataracts. Therefore, it is important to estimate the optimal UV exposure time, representing a balance between reducing negative health effects and maximizing sufficient vitamin D production. Previous studies calculated erythemal UV and vitamin-D UV from the measured and modelled spectral irradiances, respectively, by weighting CIE Erythema and Vitamin D3 generation functions (Kazantzidis et al., 2009; Fioletov et al., 2010). In particular, McKenzie et al. (2009) suggested the algorithm to estimate vitamin-D production UV from erythemal UV (or UV index) and determined the optimum conditions of UV exposure based on skin type Ⅱ according to the Fitzpatrick (1988). Recently, there are various demands for risks and benefits of surface UV radiation on public health over Korea, thus it is necessary to estimate optimal UV exposure time suitable to skin type of East Asians. This study examined the relationship between erythemally weighted UV (UVEry) and vitamin D weighted UV (UVVitD) over Korea during 2004-2012. The temporal variations of the ratio (UVVitD/UVEry) were also analyzed and the ratio as a function of UV index was applied in estimating the optimal UV exposure time. In summer with high surface UV radiation, short exposure time leaded to sufficient vitamin D and erythema and vice versa in winter. Thus, the balancing time in winter was enough to maximize UV benefits and minimize UV risks.

Simultaneously optimizing dose and schedule of a new cytotoxic agent.

PubMed

Braun, Thomas M; Thall, Peter F; Nguyen, Hoang; de Lima, Marcos

2007-01-01

Traditionally, phase I clinical trial designs are based upon one predefined course of treatment while varying among patients the dose given at each administration. In actual medical practice, patients receive a schedule comprised of several courses of treatment, and some patients may receive one or more dose reductions or delays during treatment. Consequently, the overall risk of toxicity for each patient is a function of both actual schedule of treatment and the differing doses used at each adminstration. Our goal is to provide a practical phase I clinical trial design that more accurately reflects actual medical practice by accounting for both dose per administration and schedule. We propose an outcome-adaptive Bayesian design that simultaneously optimizes both dose and schedule in terms of the overall risk of toxicity, based on time-to-toxicity outcomes. We use computer simulation as a tool to calibrate design parameters. We describe a phase I trial in allogeneic bone marrow transplantation that was designed and is currently being conducted using our new method. Our computer simulations demonstrate that our method outperforms any method that searches for an optimal dose but does not allow schedule to vary, both in terms of the probability of identifying optimal (dose, schedule) combinations, and the numbers of patients assigned to those combinations in the trial. Our design requires greater sample sizes than those seen in traditional phase I studies due to the larger number of treatment combinations examined. Our design also assumes that the effects of multiple administrations are independent of each other and that the hazard of toxicity is the same for all administrations. Our design is the first for phase I clinical trials that is sufficiently flexible and practical to truly reflect clinical practice by varying both dose and the timing and number of administrations given to each patient.

Implementation and Operational Research: A Cost-Effective, Clinically Actionable Strategy for Targeting HIV Preexposure Prophylaxis to High-Risk Men Who Have Sex With Men.

PubMed

Ross, Eric L; Cinti, Sandro K; Hutton, David W

2016-07-01

Preexposure prophylaxis (PrEP) is effective at preventing HIV infection among men who have sex with men (MSM), but there is uncertainty about how to identify high-risk MSM who should receive PrEP. We used a mathematical model to assess the cost-effectiveness of using the HIV Incidence Risk Index for MSM (HIRI-MSM) questionnaire to target PrEP to high-risk MSM. We simulated strategies of no PrEP, PrEP available to all MSM, and eligibility thresholds set to HIRI-MSM scores between 5 and 45, in increments of 5 (where a higher score predicts greater HIV risk). Based on the iPrEx, IPERGAY, and PROUD trials, we evaluated PrEP efficacies from 44% to 86% and annual costs from $5900 to 8700. We designate strategies with incremental cost-effectiveness ratio (ICER) ≤$100,000/quality-adjusted life-year (QALY) as "cost-effective." Over 20 years, making PrEP available to all MSM is projected to prevent 33.5% of new HIV infections, with an ICER of $1,474,000/QALY. Increasing the HIRI-MSM score threshold reduces the prevented infections, but improves cost-effectiveness. A threshold score of 25 is projected to be optimal (most QALYs gained while still being cost-effective) over a wide range of realistic PrEP efficacies and costs. At low cost and high efficacy (IPERGAY), thresholds of 15 or 20 are optimal across a range of other input assumptions; at high cost and low efficacy (iPrEx), 25 or 30 are generally optimal. The HIRI-MSM provides a clinically actionable means of guiding PrEP use. Using a score of 25 to determine PrEP eligibility could facilitate cost-effective use of PrEP among high-risk MSM who will benefit from it most.

A Retrospective Analysis of Pressure Ulcer Incidence and Modified Braden Scale Score Risk Classifications.

PubMed

Chen, Hong-Lin; Cao, Ying-Juan; Wang, Jing; Huai, Bao-Sha

2015-09-01

The Braden Scale is the most widely used pressure ulcer risk assessment in the world, but the currently used 5 risk classification groups do not accurately discriminate among their risk categories. To optimize risk classification based on Braden Scale scores, a retrospective analysis of all consecutively admitted patients in an acute care facility who were at risk for pressure ulcer development was performed between January 2013 and December 2013. Predicted pressure ulcer incidence first was calculated by logistic regression model based on original Braden score. Risk classification then was modified based on the predicted pressure ulcer incidence and compared between different risk categories in the modified (3-group) classification and the traditional (5-group) classification using chi-square test. Two thousand, six hundred, twenty-five (2,625) patients (mean age 59.8 ± 16.5, range 1 month to 98 years, 1,601 of whom were men) were included in the study; 81 patients (3.1%) developed a pressure ulcer. The predicted pressure ulcer incidence ranged from 0.1% to 49.7%. When the predicted pressure ulcer incidence was greater than 10.0% (high risk), the corresponding Braden scores were less than 11; when the predicted incidence ranged from 1.0% to 10.0% (moderate risk), the corresponding Braden scores ranged from 12 to 16; and when the predicted incidence was less than 1.0% (mild risk), the corresponding Braden scores were greater than 17. In the modified classification, observed pressure ulcer incidence was significantly different between each of the 3 risk categories (P less than 0.05). However, in the traditional classification, the observed incidence was not significantly different between the high-risk category and moderate-risk category (P less than 0.05) and between the mild-risk category and no-risk category (P less than 0.05). If future studies confirm the validity of these findings, pressure ulcer prevention protocols of care based on Braden Scale scores can be simplified.

Relationship between compliance and persistence with osteoporosis medications and fracture risk in primary health care in France: a retrospective case-control analysis.

PubMed

Cotté, François-Emery; Mercier, Florence; De Pouvourville, Gérard

2008-12-01

Nonadherence to treatment is an important determinant of long-term outcomes in women with osteoporosis. This study was conducted to investigate the association between adherence and osteoporotic fracture risk and to identify optimal thresholds for good compliance and persistence. A secondary objective was to perform a preliminary evaluation of the cost consequences of adherence. This was a retrospective case-control analysis. Data were derived from the Thales prescription database, which contains information on >1.6 million patients in the primary health care setting in France. Cases were women aged >or=50 years who had an osteoporosis-related fracture in 2006. For each case, 5 matched controls were randomly selected. Both compliance and persistence aspects of treatment adherence were examined. Compliance was estimated based on the medication possession ratio (MPR). Persistence was calculated as the time from the initial filling of a prescription for osteoporosis medication until its discontinuation. The mean (SD) MPR was lower in cases compared with controls (58.8% [34.7%] vs 72.1% [28.8%], respectively; P < 0.001). Cases were more likely than controls to discontinue osteoporosis treatment (50.0% vs 25.3%; P < 0.001), yielding a significantly lower proportion of patients who were still persistent at 1 year (34.1% vs 40.9%; P < 0.001). MPR was the best predictor of fracture risk, with an area under the receiver-operating-characteristic curve that was higher than that for persistence (0.59 vs 0.55). The optimal MPR threshold for predicting fracture risk was >or=68.0%. Compared with less-compliant women, women who achieved this threshold had a 51% reduction in fracture risk. The difference in annual drug expenditure between women achieving this threshold and those who did not was approximately euro300. The optimal threshold for persistence with therapy was at least 6 months. Attaining this threshold was associated with a 28% reduction in fracture risk compared with less-persistent women. In this study, better treatment adherence was associated with a greater reduction in fracture risk. Compliance appeared to predict fracture risk better than did persistence.

WE-DE-201-01: BEST IN PHYSICS (THERAPY): A Fast Multi-Target Inverse Treatment Planning Strategy Optimizing Dosimetric Measures for High-Dose-Rate (HDR) Brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guthier, C; University Medical Center Mannheim, Mannheim; Harvard Medical School, Boston, MA

Purpose: Inverse treatment planning (ITP) for interstitial HDR brachytherapy of gynecologic cancers seeks to maximize coverage of the clinical target volumes (tumor and vagina) while respecting dose-volume-histogram related dosimetric measures (DMs) for organs at risk (OARs). Commercially available ITP tools do not support DM-based planning because it is computationally too expensive to solve. In this study we present a novel approach that allows fast ITP for gynecologic cancers based on DMs for the first time. Methods: This novel strategy is an optimization model based on a smooth DM-based objective function. The smooth approximation is achieved by utilizing a logistic functionmore » for the evaluation of DMs. The resulting nonconvex and constrained optimization problem is then optimized with a BFGS algorithm. The model was evaluated using the implant geometry extracted from 20 patient treatment plans under an IRB-approved retrospective study. For each plan, the final DMs were evaluated and compared to the original clinical plans. The CTVs were the contoured tumor volume and the contoured surface of the vagina. Statistical significance was evaluated with a one-sided paired Wilcoxon signed-rank test. Results: As did the clinical plans, all generated plans fulfilled the defined DMs for OARs. The proposed strategy showed a statistically significant improvement (p<0.001) in coverage of the tumor and vagina, with absolute improvements of related DMs of (6.9 +/− 7.9)% and (28.2 +/− 12.0)%, respectively. This was achieved with a statistically significant (p<0.01) decrease of the high-dose-related DM for the tumor. The runtime of the optimization was (2.3 +/− 2.0) seconds. Conclusion: We demonstrated using clinical data that our novel approach allows rapid DM-based optimization with improved coverage of CTVs with fewer hot spots. Being up to three orders of magnitude faster than the current clinical practice, the method dramatically shortens planning time.« less

Optimization Under Uncertainty of Site-Specific Turbine Configurations

NASA Astrophysics Data System (ADS)

Quick, J.; Dykes, K.; Graf, P.; Zahle, F.

2016-09-01

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained with increasing risk aversion on the part of the designer.

Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions.

PubMed

Price, Bertram; MacNicoll, Michael

2015-05-01

A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed. © 2015 Society for Risk Analysis.

A point-based prediction model for cardiovascular risk in orthotopic liver transplantation: The CAR-OLT score.

PubMed

VanWagner, Lisa B; Ning, Hongyan; Whitsett, Maureen; Levitsky, Josh; Uttal, Sarah; Wilkins, John T; Abecassis, Michael M; Ladner, Daniela P; Skaro, Anton I; Lloyd-Jones, Donald M

2017-12-01

Cardiovascular disease (CVD) complications are important causes of morbidity and mortality after orthotopic liver transplantation (OLT). There is currently no preoperative risk-assessment tool that allows physicians to estimate the risk for CVD events following OLT. We sought to develop a point-based prediction model (risk score) for CVD complications after OLT, the Cardiovascular Risk in Orthotopic Liver Transplantation risk score, among a cohort of 1,024 consecutive patients aged 18-75 years who underwent first OLT in a tertiary-care teaching hospital (2002-2011). The main outcome measures were major 1-year CVD complications, defined as death from a CVD cause or hospitalization for a major CVD event (myocardial infarction, revascularization, heart failure, atrial fibrillation, cardiac arrest, pulmonary embolism, and/or stroke). The bootstrap method yielded bias-corrected 95% confidence intervals for the regression coefficients of the final model. Among 1,024 first OLT recipients, major CVD complications occurred in 329 (32.1%). Variables selected for inclusion in the model (using model optimization strategies) included preoperative recipient age, sex, race, employment status, education status, history of hepatocellular carcinoma, diabetes, heart failure, atrial fibrillation, pulmonary or systemic hypertension, and respiratory failure. The discriminative performance of the point-based score (C statistic = 0.78, bias-corrected C statistic = 0.77) was superior to other published risk models for postoperative CVD morbidity and mortality, and it had appropriate calibration (Hosmer-Lemeshow P = 0.33). The point-based risk score can identify patients at risk for CVD complications after OLT surgery (available at www.carolt.us); this score may be useful for identification of candidates for further risk stratification or other management strategies to improve CVD outcomes after OLT. (Hepatology 2017;66:1968-1979). © 2017 by the American Association for the Study of Liver Diseases.

Advanced Endoscopic Imaging for Surveillance for Dysplasia and Colorectal Cancer in inflammatory Bowel Disease: Could the Pathologist be Further Helped?

PubMed Central

Sinagra, Emanuele; Tomasello, Giovanni; Raimondo, Dario; Sturm, Andreas; Giunta, Marco; Messina, Marco; Damiano, Giuseppe; Palumbo, Vincenzo D.; Spinelli, Gabriele; Rossi, Francesca; Facella, Tiziana; Marasà, Salvatore; Cottone, Mario; Lo Monte, Attilio I.

2014-01-01

Patients with inflammatory bowel disease (IBD) have an increased risk of developing intestinal cancer. The magnitude of that increased risk as well as how best to mitigate it remain a topic of ongoing investigation in the field. It is important to quantify the risk of colorectal cancer in association with IBD. The reported risk varies widely between studies. This is partly due to the different methodologies used in the studies. Because of the limitations of surveillance strategies based on the detection of dysplasia, advanced endoscopic imaging and techniques involving the detection of alterations in mucosal antigens and genetic abnormalities are being investigated. Development of new biomarkers, predicting future occurrence of colonic neoplasia may lead to more biomarker-based surveillance. There are promising results that may lead to more efficient surveillance in IBD patients and more general acceptance of its use. A multidisciplinary approach, involving in particular endoscopists and pathologists, together with a centralized patient management, could help to optimize treatments and follow-up measures, both of which could help to reduce the IBD-associated cancer risk. PMID:24496155

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Hirt, Evelyn H.; Dib, Gerges

This project involved the development of enhanced risk monitors (ERMs) for active components in Advanced Reactor (AdvRx) designs by integrating real-time information about equipment condition with risk monitors. Health monitoring techniques in combination with predictive estimates of component failure based on condition and risk monitors can serve to indicate the risk posed by continued operation in the presence of detected degradation. This combination of predictive health monitoring based on equipment condition assessment and risk monitors can also enable optimization of maintenance scheduling with respect to the economics of plant operation. This report summarizes PNNL’s multi-year project on the development andmore » evaluation of an ERM concept for active components while highlighting FY2016 accomplishments. Specifically, this report provides a status summary of the integration and demonstration of the prototypic ERM framework with the plant supervisory control algorithms being developed at Oak Ridge National Laboratory (ORNL), and describes additional case studies conducted to assess sensitivity of the technology to different quantities. Supporting documentation on the software package to be provided to ONRL is incorporated in this report.« less

Optimization of monopiles for offshore wind turbines.

PubMed

Kallehave, Dan; Byrne, Byron W; LeBlanc Thilsted, Christian; Mikkelsen, Kristian Kousgaard

2015-02-28

The offshore wind industry currently relies on subsidy schemes to be competitive with fossil-fuel-based energy sources. For the wind industry to survive, it is vital that costs are significantly reduced for future projects. This can be partly achieved by introducing new technologies and partly through optimization of existing technologies and design methods. One of the areas where costs can be reduced is in the support structure, where better designs, cheaper fabrication and quicker installation might all be possible. The prevailing support structure design is the monopile structure, where the simple design is well suited to mass-fabrication, and the installation approach, based on conventional impact driving, is relatively low-risk and robust for most soil conditions. The range of application of the monopile for future wind farms can be extended by using more accurate engineering design methods, specifically tailored to offshore wind industry design. This paper describes how state-of-the-art optimization approaches are applied to the design of current wind farms and monopile support structures and identifies the main drivers where more accurate engineering methods could impact on a next generation of highly optimized monopiles. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Delivery at Term: When, How, and Why.

PubMed

Walker, Kate F; Thornton, Jim G

2018-06-01

There is growing evidence from randomized trials that induction of labor at or near term does not increase cesarean delivery; observational data show that the optimal gestation for spontaneous delivery for the baby is 39 weeks. Elective cesarean at these gestations is also sometimes considered, but evaluating the associated risks is complex. For the baby, although cesarean obviates the risks of labor, it carries a risk of respiratory problems, which may be severe. For the mother, cesarean is more dangerous than vaginal and emergency cesarean is more dangerous than elective. The authors consider the evidence base for near-term induction of labor and cesarean for a range of scenarios. Copyright © 2018 Elsevier Inc. All rights reserved.

Applying a Geospatial Visualization Based on USSD Messages to Real Time Identification of Epidemiological Risk Areas in Developing Countries: A Case of Study of Paraguay.

PubMed

Ochoa, Silvia; Talavera, Julia; Paciello, Julio

2015-01-01

The identification of epidemiological risk areas is one of the major problems in public health. Information management strategies are needed to facilitate prevention and control of disease in the affected areas. This paper presents a model to optimize geographical data collection of suspected or confirmed disease occurrences using the Unstructured Supplementary Service Data (USSD) mobile technology, considering its wide adoption even in developing countries such as Paraguay. A Geographic Information System (GIS) is proposed for visualizing potential epidemiological risk areas in real time, that aims to support decision making and to implement prevention or contingency programs for public health.

Implementation of "Quality by Design (QbD)" Approach for the Development of 5-Fluorouracil Loaded Thermosensitive Hydrogel.

PubMed

Dalwadi, Chintan; Patel, Gayatri

2016-01-01

The purpose of this study was to investigate Quality by Design (QbD) principle for the preparation of hydrogel products to prove both practicability and utility of executing QbD concept to hydrogel based controlled release systems. Product and process understanding will help in decreasing the variability of critical material and process parameters, which give quality product output and reduce the risk. This study includes the identification of the Quality Target Product Profiles (QTPPs) and Critical Quality Attributes (CQAs) from literature or preliminary studies. To identify and control the variability in process and material attributes, two tools of QbD was utilized, Quality Risk Management (QRM) and Experimental Design. Further, it helps to identify the effect of these attributes on CQAs. Potential risk factors were identified from fishbone diagram and screened by risk assessment and optimized by 3-level 2- factor experimental design with center points in triplicate, to analyze the precision of the target process. This optimized formulation was further characterized by gelling time, gelling temperature, rheological parameters, in-vitro biodegradation and in-vitro drug release. Design space was created using experimental design tool that gives the control space and working within this controlled space reduces all the failure modes below the risk level. In conclusion, QbD approach with QRM tool provides potent and effectual pyramid to enhance the quality into the hydrogel.

Integrated biodepuration of pesticide-contaminated wastewaters from the fruit-packaging industry using biobeds: Bioaugmentation, risk assessment and optimized management.

PubMed

Karas, Panagiotis A; Perruchon, Chiara; Karanasios, Evangelos; Papadopoulou, Evangelia S; Manthou, Elena; Sitra, Stefania; Ehaliotis, Constantinos; Karpouzas, Dimitrios G

2016-12-15

Wastewaters from fruit-packaging plants contain high loads of toxic and persistent pesticides and should be treated on site. We evaluated the depuration performance of five pilot biobeds against those effluents. In addition we tested bioaugmentation with bacterial inocula as a strategy for optimization of their depuration capacity. Finally we determined the composition and functional dynamics of the microbial community via q-PCR. Practical issues were also addressed including the risk associated with the direct environmental disposal of biobed-treated effluents and decontamination methods for the spent packing material. Biobeds showed high depuration capacity (>99.5%) against all pesticides with bioaugmentation maximizing their depuration performance against the persistent fungicide thiabendazole (TBZ). This was followed by a significant increase in the abundance of bacteria, fungi and of catabolic genes of aromatic compounds catA and pcaH. Bioaugmentation was the most potent decontamination method for spent packing material with composting being an effective alternative. Risk assessment based on practical scenarios (pome and citrus fruit-packaging plants) and the depuration performance of the pilot biobeds showed that discharge of the treated effluents into an 0.1-ha disposal site did not entail an environmental risk, except for TBZ-containing effluents where a larger disposal area (0.2ha) or bioaugmentation alleviated the risk. Copyright © 2016 Elsevier B.V. All rights reserved.

Scalability of a Methodology for Generating Technical Trading Rules with GAPs Based on Risk-Return Adjustment and Incremental Training

NASA Astrophysics Data System (ADS)

de La Cal, E. A.; Fernández, E. M.; Quiroga, R.; Villar, J. R.; Sedano, J.

In previous works a methodology was defined, based on the design of a genetic algorithm GAP and an incremental training technique adapted to the learning of series of stock market values. The GAP technique consists in a fusion of GP and GA. The GAP algorithm implements the automatic search for crisp trading rules taking as objectives of the training both the optimization of the return obtained and the minimization of the assumed risk. Applying the proposed methodology, rules have been obtained for a period of eight years of the S&P500 index. The achieved adjustment of the relation return-risk has generated rules with returns very superior in the testing period to those obtained applying habitual methodologies and even clearly superior to Buy&Hold. This work probes that the proposed methodology is valid for different assets in a different market than previous work.

Excessive Exercise in Endurance Athletes: Is Atrial Fibrillation a Possible Consequence?

PubMed

Goodman, Jack M; Banks, Laura; Connelly, Kim A; Yan, Andrew; Backx, Peter H; Dorian, Paul

2018-05-29

Moderate physical activity levels are associated with increased longevity and lower risk of atrial fibrillation (AF). However, the relative risk of lone AF is 3-5 fold higher in intensive endurance-trained athletes compared to healthy adults. There is growing concern that 'excessive' endurance exercise may promote cardiac remodeling leading to long-term adverse consequences. The pathogenesis of exercise-induced AF is thought to arise from an interplay of multiple acute and chronic factors, including atrial enlargement, pro-fibrotic tendency, high vagal tone, and genotypic profile, which collectively promote adverse atrial remodeling. Clinical management of athletes with AF, while challenging, can be achieved using various strategies that may allow continued, safe exercise. Based on the overall risk-benefit evidence, it is premature to suggest 'excessive' exercise is unsafe or should be curtailed. Evidence-based assessment and treatment guidelines are required to ensure optimal and safe exercise among the growing number of endurance athletes with AF.

Sex-based Differences in Common Sports Injuries.

PubMed

Carter, Cordelia W; Ireland, Mary Lloyd; Johnson, Anthony E; Levine, William N; Martin, Scott; Bedi, Asheesh; Matzkin, Elizabeth G

2018-05-28

The patient's sex plays an important role in mediating the risk for, and experience of, disease. Injuries of the musculoskeletal system are no exception to this phenomenon. Increasing evidence shows that the incidence, clinical presentation, and treatment outcomes for male and female patients with common sports injuries may vary widely. Stress fracture, which is associated with the female athlete triad, is a sports injury with known sex-based differences. Other common sports-related injuries may also have distinct sex-based differences. Understanding these differences is important to optimize each patient's musculoskeletal care.

A practical method of I-131 thyroid cancer therapy dose optimization using estimated effective renal clearance.

PubMed

Howard, Brandon A; James, Olga G; Perkins, Jennifer M; Pagnanelli, Robert A; Borges-Neto, Salvador; Reiman, Robert E

2017-01-01

In thyroid cancer patients with renal impairment or other complicating factors, it is important to maximize I-131 therapy efficacy while minimizing bone marrow and lung damage. We developed a web-based calculator based on a modified Benua and Leeper method to calculate the maximum I-131 dose to reduce the risk of these toxicities, based on the effective renal clearance of I-123 as measured from two whole-body I-123 scans, performed at 0 and 24 h post-administration.

Accuracy and adequacy of waist circumference cut-off points currently recommended in Brazilian adults.

PubMed

Vianna, Carolina Avila; da Silva Linhares, Rogério; Bielemann, Renata Moraes; Machado, Eduardo Coelho; González-Chica, David Alejandro; Matijasevich, Alicia Manitto; Gigante, Denise Petrucci; da Silva Dos Santos, Iná

2014-04-01

To evaluate the adequacy and accuracy of cut-off values currently recommended by the WHO for assessment of cardiovascular risk in southern Brazil. Population-based study aimed at determining the predictive ability of waist circumference for cardiovascular risk based on the use of previous medical diagnosis for hypertension, diabetes mellitus and/or dyslipidaemia. Descriptive analysis was used for the adequacy of current cut-off values of waist circumference, receiver operating characteristic curves were constructed and the most accurate criteria according to the Youden index and points of optimal sensitivity and specificity were identified. Pelotas, southern Brazil. Individuals (n 2112) aged ≥20 years living in the city were selected by multistage sampling, since these individuals did not report the presence of previous myocardial infarction, angina pectoris or stroke. The cut-off values currently recommended by WHO were more appropriate in men than women, with overestimation of cardiovascular risk in women. The area under the receiver operating characteristic curve showed moderate predictive ability of waist circumference in men (0.74, 95% CI 0.71, 0.76) and women (0.75, 95% CI 0.73, 0.77). The method of optimal sensitivity and specificity showed better performance in assessing the accuracy, identifying the values of 95 cm in men and 87 cm in women as the best cut-off values of waist circumference to assess cardiovascular risk. The cut-off values currently recommended for waist circumference are not suitable for women. Longitudinal studies should be conducted to evaluate the consistency of the findings.

A two-stage optimization model for emergency material reserve layout planning under uncertainty in response to environmental accidents.

PubMed

Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Liu, Rentao; Wang, Peng

2016-06-05

In the emergency management relevant to pollution accidents, efficiency emergency rescues can be deeply influenced by a reasonable assignment of the available emergency materials to the related risk sources. In this study, a two-stage optimization framework is developed for emergency material reserve layout planning under uncertainty to identify material warehouse locations and emergency material reserve schemes in pre-accident phase coping with potential environmental accidents. This framework is based on an integration of Hierarchical clustering analysis - improved center of gravity (HCA-ICG) model and material warehouse location - emergency material allocation (MWL-EMA) model. First, decision alternatives are generated using HCA-ICG to identify newly-built emergency material warehouses for risk sources which cannot be satisfied by existing ones with a time-effective manner. Second, emergency material reserve planning is obtained using MWL-EMA to make emergency materials be prepared in advance with a cost-effective manner. The optimization framework is then applied to emergency management system planning in Jiangsu province, China. The results demonstrate that the developed framework not only could facilitate material warehouse selection but also effectively provide emergency material for emergency operations in a quick response. Copyright © 2016. Published by Elsevier B.V.

Progress in violence risk assessment and communication: hypothesis versus evidence.

PubMed

Harris, Grant T; Rice, Marnie E

2015-02-01

We draw a distinction between hypothesis and evidence with respect to the assessment and communication of the risk of violent recidivism. We suggest that some authorities in the field have proposed quite valid and reasonable hypotheses with respect to several issues. Among these are the following: that accuracy will be improved by the adjustment or moderation of numerical scores based on clinical opinions about rare risk factors or other considerations pertaining to the applicability to the case at hand; that there is something fundamentally distinct about protective factors so that they are not merely the obverse of risk factors, such that optimal accuracy cannot be achieved without consideration of such protective factors; and that assessment of dynamic factors is required for optimal accuracy and furthermore interventions aimed at such dynamic factors can be expected to cause reductions in violence risk. We suggest here that, while these are generally reasonable hypotheses, they have been inappropriately presented to practitioners as empirically supported facts, and that practitioners' assessment and communication about violence risk run beyond that supported by the available evidence as a result. We further suggest that this represents harm, especially in impeding scientific progress. Nothing here justifies stasis or simply surrendering to authoritarian custody with somatic treatment. Theoretically motivated and clearly articulated assessment and intervention should be provided for offenders, but in a manner that moves the field more firmly from hypotheses to evidence. Copyright © 2015 John Wiley & Sons, Ltd.

Risks and injuries in laser and high-frequency applications

NASA Astrophysics Data System (ADS)

Giering, K.; Philipp, Carsten M.; Berlien, Hans-Peter

1995-01-01

An analysis of injuries and risks using high frequency (HF) and lasers in medicine based on a literature search with MEDLINE was performed. The cases reported in the literature were classified according to the following criteria: (1) Avoidable in an optimal operational procedure. These kind of injuries are caused by a chain of unfortunate incidents. They are in principle avoidable by the 'right action at the right time' which presupposes an appropriate training of the operating team, selection of the optimal parameters for procedure and consideration of all safety instructions. (2) Avoidable, caused by malfunction of the equipment and/or accessories. The injuries classified into this group are avoidable if all safety regulations were fulfilled. This includes a pre-operational check-up and the use of medical lasers and high frequency devices only which meet the international safety standards. (3) Avoidable, caused by misuse/mistake. Injuries of this group were caused by an inappropriate selection of the procedure, wrong medical indication or mistakes during application. (4) Unavoidable, fateful. These injuries can be caused by risks inherent to the type of energy used, malfunction of the equipment and/or accessories though a pre-operational check-up was done. Some risks and complications are common to high frequency and laser application. But whereas these risks can be excluded easily in laser surgery there is often a great expenditure necessary or they are not avoidable if high frequency if used. No unavoidable risks due to laser energy occur.

Improving the prognosis of patients with severely decreased glomerular filtration rate (CKD G4+): conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference

PubMed Central

Eckardt, Kai-Uwe; Bansal, Nisha; Coresh, Josef; Evans, Marie; Grams, Morgan E.; Herzog, Charles A.; James, Matthew T.; Heerspink, Hiddo J.L.; Pollock, Carol A.; Stevens, Paul E.; Tamura, Manjula Kurella; Tonelli, Marcello A.; Wheeler, David C.; Winkelmayer, Wolfgang C.; Cheung, Michael; Hemmelgarn, Brenda R.

2018-01-01

Patients with severely decreased glomerular filtration rate (GFR) (i.e., chronic kidney disease [CKD] G4+) are at increased risk for kidney failure, cardiovascular disease (CVD) events (including heart failure), and death. However, little is known about the variability of outcomes and optimal therapeutic strategies, including initiation of kidney replacement therapy (KRT). Kidney Disease: Improving Global Outcomes (KDIGO) organized a Controversies Conference with an international expert group in December 2016 to address this gap in knowledge. In collaboration with the CKD Prognosis Consortium (CKD-PC) a global meta-analysis of cohort studies (n = 264,515 individuals with CKD G4+) was conducted to better understand the timing of clinical outcomes in patients with CKD G4+ and risk factors for different outcomes. The results confirmed the prognostic value of traditional CVD risk factors in individuals with severely decreased GFR, although the risk estimates vary for kidney and CVD outcomes. A 2- and 4-year model of the probability and timing of kidney failure requiring KRT was also developed. The implications of these findings for patient management were discussed in the context of published evidence under 4 key themes: management of CKD G4+, diagnostic and therapeutic challenges of heart failure, shared decision-making, and optimization of clinical trials in CKD G4+ patients. Participants concluded that variable prognosis of patients with advanced CKD mandates individualized, risk-based management, factoring in competing risks and patient preferences. PMID:29656903

Evaluation of machine learning algorithms for improved risk assessment for Down's syndrome.

PubMed

Koivu, Aki; Korpimäki, Teemu; Kivelä, Petri; Pahikkala, Tapio; Sairanen, Mikko

2018-05-04

Prenatal screening generates a great amount of data that is used for predicting risk of various disorders. Prenatal risk assessment is based on multiple clinical variables and overall performance is defined by how well the risk algorithm is optimized for the population in question. This article evaluates machine learning algorithms to improve performance of first trimester screening of Down syndrome. Machine learning algorithms pose an adaptive alternative to develop better risk assessment models using the existing clinical variables. Two real-world data sets were used to experiment with multiple classification algorithms. Implemented models were tested with a third, real-world, data set and performance was compared to a predicate method, a commercial risk assessment software. Best performing deep neural network model gave an area under the curve of 0.96 and detection rate of 78% with 1% false positive rate with the test data. Support vector machine model gave area under the curve of 0.95 and detection rate of 61% with 1% false positive rate with the same test data. When compared with the predicate method, the best support vector machine model was slightly inferior, but an optimized deep neural network model was able to give higher detection rates with same false positive rate or similar detection rate but with markedly lower false positive rate. This finding could further improve the first trimester screening for Down syndrome, by using existing clinical variables and a large training data derived from a specific population. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

NASA Technical Reports Server (NTRS)

Kerstman, Eric; Minard, Charles; Saile, Lynn; deCarvalho, Mary Freire; Myers, Jerry; Walton, Marlei; Butler, Douglas; Iyengar, Sriram; Johnson-Throop, Kathy; Baumann, David

2009-01-01

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China.

PubMed

Di, Hui; Liu, Xingpeng; Zhang, Jiquan; Tong, Zhijun; Ji, Meichen

2018-03-15

Water environmental risk is the probability of the occurrence of events caused by human activities or the interaction of human activities and natural processes that will damage a water environment. This study proposed a water environmental risk index (WERI) model to assess the water environmental risk in the Yinma River Basin based on hazards, exposure, vulnerability, and regional management ability indicators in a water environment. The data for each indicator were gathered from 2000, 2005, 2010, and 2015 to assess the spatial and temporal variations in water environmental risk using particle swarm optimization and the analytic hierarchy process (PSO-AHP) method. The results showed that the water environmental risk in the Yinma River Basin decreased from 2000 to 2015. The risk level of the water environment was high in Changchun, while the risk levels in Yitong and Yongji were low. The research methods provide information to support future decision making by the risk managers in the Yinma River Basin, which is in a high-risk water environment. Moreover, water environment managers could reduce the risks by adjusting the indicators that affect water environmental risks.

Relevance of immobility and importance of risk assessment management for medically ill patients.

PubMed

Hull, Russell D

2013-06-01

Recent or continued immobility is a significant risk factor for venous thromboembolism (VTE) in acutely ill medical patients. Patients may benefit from thromboprophylaxis; however, its optimal duration remains unclear. The Extended Clinical Prophylaxis in Acutely Ill Medical Patients (EXCLAIM) study was the first trial to systematically investigate how the degree of immobilization relates to the risk of developing VTE. EXCLAIM offers insights into the duration of VTE risk associated with reduced mobility and helps identify which patients would benefit most from extended-duration thromboprophylaxis. Further recent studies suggest that extended-duration thromboprophylaxis may be in order in certain high-risk patients to protect the patients from the risk of VTE events occurring, particularly in the posthospitalization period. Baseline d-dimer data and level of mobility could be included in risk assessment. Physicians are recommended to consider the use of extended-duration thromboprophylaxis based on individual risk assessment management (RAM) and balance of benefit and harm.

Current role of sodium bicarbonate-based preprocedural hydration for the prevention of contrast-induced acute kidney injury: a meta-analysis.

PubMed

Hogan, Shea E; L'Allier, Phillipe; Chetcuti, Stanley; Grossman, P Michael; Nallamothu, Brahmajee K; Duvernoy, Claire; Bates, Eric; Moscucci, Mauro; Gurm, Hitinder S

2008-09-01

The optimal hydration strategy for prevention of contrast-induced acute kidney injury (AKI) remains unknown. The purpose of this meta-analysis is to compare the effectiveness of normal saline (NS) versus sodium bicarbonate hydration (NaHCO(3)) for prevention of contrast-induced AKI. We performed a meta-analysis of randomized controlled trials that compared saline-based hydration with sodium bicarbonate-based hydration regimen for prophylaxis of contrast-induced AKI. The literature search included MEDLINE, EMBASE, and Cochrane databases (2000 to October 2007); conference proceedings; and bibliographies of retrieved articles. Information was extracted on study design, sample characteristics, and interventions. Random-effects models were used to calculate summary risk ratios for contrast-induced AKI, need for hemodialysis, and death. Seven trials with 1,307 subjects were included. Preprocedural hydration with sodium bicarbonate was associated with a significant decrease in the rate of contrast-induced AKI (5.96% in the NaHCO(3) arm versus 17.23% in the NS arm, summary risk ratio 0.37, 95% CI 0.18-0.714, P = .005). There was no difference in the rates of postprocedure hemodialysis or death. Formal testing revealed moderate heterogeneity and a strong likelihood of publication bias. Although sodium bicarbonate hydration was found to be superior to NS in prevention of contrast-induced AKI, these results are in the context of study heterogeneity and, likely, publication bias. An adequately powered randomized controlled trial is warranted to define the optimal hydration strategy in patients at high risk of contrast-induced AKI who are scheduled to undergo contrast administration.

Optimization of human, animal, and environmental health by using the One Health approach.

PubMed

Sleeman, Jonathan M; DeLiberto, Thomas; Nguyen, Natalie

2017-08-31

Emerging diseases are increasing burdens on public health, negatively affecting the world economy, causing extinction of species, and disrupting ecological integrity. One Health recognizes that human, domestic animal, and wildlife health are interconnected within ecosystem health and provides a framework for the development of multidisciplinary solutions to global health challenges. To date, most health-promoting interventions have focused largely on single-sector outcomes. For example, risk for transmission of zoonotic pathogens from bush-meat hunting is primarily focused on human hygiene and personal protection. However, bush-meat hunting is a complex issue promoting the need for holistic strategies to reduce transmission of zoonotic disease while addressing food security and wildlife conservation issues. Temporal and spatial separation of humans and wildlife, risk communication, and other preventative strategies should allow wildlife and humans to co-exist. Upstream surveillance, vaccination, and other tools to prevent pathogen spillover are also needed. Clear multi-sector outcomes should be defined, and a systems-based approach is needed to develop interventions that reduce risks and balance the needs of humans, wildlife, and the environment. The ultimate goal is long-term action to reduce forces driving emerging diseases and provide interdisciplinary scientific approaches to management of risks, thereby achieving optimal outcomes for human, animal, and environmental health.

Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR).

PubMed

Evans, Scott R; Rubin, Daniel; Follmann, Dean; Pennello, Gene; Huskins, W Charles; Powers, John H; Schoenfeld, David; Chuang-Stein, Christy; Cosgrove, Sara E; Fowler, Vance G; Lautenbach, Ebbing; Chambers, Henry F

2015-09-01

Clinical trials that compare strategies to optimize antibiotic use are of critical importance but are limited by competing risks that distort outcome interpretation, complexities of noninferiority trials, large sample sizes, and inadequate evaluation of benefits and harms at the patient level. The Antibacterial Resistance Leadership Group strives to overcome these challenges through innovative trial design. Response adjusted for duration of antibiotic risk (RADAR) is a novel methodology utilizing a superiority design and a 2-step process: (1) categorizing patients into an overall clinical outcome (based on benefits and harms), and (2) ranking patients with respect to a desirability of outcome ranking (DOOR). DOORs are constructed by assigning higher ranks to patients with (1) better overall clinical outcomes and (2) shorter durations of antibiotic use for similar overall clinical outcomes. DOOR distributions are compared between antibiotic use strategies. The probability that a randomly selected patient will have a better DOOR if assigned to the new strategy is estimated. DOOR/RADAR represents a new paradigm in assessing the risks and benefits of new strategies to optimize antibiotic use. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Sexual behavior, risk perception, and HIV transmission can respond to HIV antiviral drugs and vaccines through multiple pathways.

PubMed

Tully, Stephen; Cojocaru, Monica; Bauch, Chris T

2015-10-28

There has been growing use of highly active antiretroviral treatment (HAART) for HIV and significant progress in developing prophylactic HIV vaccines. The simplest theories of counterproductive behavioral responses to such interventions tend to focus on single feedback mechanisms: for instance, HAART optimism makes infection less scary and thus promotes risky sexual behavior. Here, we develop an agent based, age-structured model of HIV transmission, risk perception, and partner selection in a core group to explore behavioral responses to interventions. We find that interventions can activate not one, but several feedback mechanisms that could potentially influence decision-making and HIV prevalence. In the model, HAART increases the attractiveness of unprotected sex, but it also increases perceived risk of infection and, on longer timescales, causes demographic impacts that partially counteract HAART optimism. Both HAART and vaccination usually lead to lower rates of unprotected sex on the whole, but intervention effectiveness depends strongly on whether individuals over- or under-estimate intervention coverage. Age-specific effects cause sexual behavior and HIV prevalence to change in opposite ways in old and young age groups. For complex infections like HIV-where interventions influence transmission, demography, sexual behavior and risk perception-we conclude that evaluations of behavioral responses should consider multiple feedback mechanisms.

Optimization of human, animal, and environmental health by using the One Health approach

USGS Publications Warehouse

Sleeman, Jonathan M.; DeLiberto, Thomas; Nguyen, Natalie T.

2017-01-01

Emerging diseases are increasing burdens on public health, negatively affecting the world economy, causing extinction of species, and disrupting ecological integrity. One Health recognizes that human, domestic animal, and wildlife health are interconnected within ecosystem health and provides a framework for the development of multidisciplinary solutions to global health challenges. To date, most health-promoting interventions have focused largely on single-sector outcomes. For example, risk for transmission of zoonotic pathogens from bush-meat hunting is primarily focused on human hygiene and personal protection. However, bush-meat hunting is a complex issue promoting the need for holistic strategies to reduce transmission of zoonotic disease while addressing food security and wildlife conservation issues. Temporal and spatial separation of humans and wildlife, risk communication, and other preventative strategies should allow wildlife and humans to co-exist. Upstream surveillance, vaccination, and other tools to prevent pathogen spillover are also needed. Clear multi-sector outcomes should be defined, and a systems-based approach is needed to develop interventions that reduce risks and balance the needs of humans, wildlife, and the environment. The ultimate goal is long-term action to reduce forces driving emerging diseases and provide interdisciplinary scientific approaches to management of risks, thereby achieving optimal outcomes for human, animal, and environmental health.

The returns and risks of investment portfolio in stock market crashes

NASA Astrophysics Data System (ADS)

Li, Jiang-Cheng; Long, Chao; Chen, Xiao-Dan

2015-06-01

The returns and risks of investment portfolio in stock market crashes are investigated by considering a theoretical model, based on a modified Heston model with a cubic nonlinearity, proposed by Spagnolo and Valenti. Through numerically simulating probability density function of returns and the mean escape time of the model, the results indicate that: (i) the maximum stability of returns is associated with the maximum dispersion of investment portfolio and an optimal stop-loss position; (ii) the maximum risks are related with a worst dispersion of investment portfolio and the risks of investment portfolio are enhanced by increasing stop-loss position. In addition, the good agreements between the theoretical result and real market data are found in the behaviors of the probability density function and the mean escape time.

Influence of Injury Risk Thresholds on the Performance of an Algorithm to Predict Crashes with Serious Injuries

PubMed Central

Bahouth, George; Digges, Kennerly; Schulman, Carl

2012-01-01

This paper presents methods to estimate crash injury risk based on crash characteristics captured by some passenger vehicles equipped with Advanced Automatic Crash Notification technology. The resulting injury risk estimates could be used within an algorithm to optimize rescue care. Regression analysis was applied to the National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) to determine how variations in a specific injury risk threshold would influence the accuracy of predicting crashes with serious injuries. The recommended thresholds for classifying crashes with severe injuries are 0.10 for frontal crashes and 0.05 for side crashes. The regression analysis of NASS/CDS indicates that these thresholds will provide sensitivity above 0.67 while maintaining a positive predictive value in the range of 0.20. PMID:23169132

Mean-deviation analysis in the theory of choice.

PubMed

Grechuk, Bogdan; Molyboha, Anton; Zabarankin, Michael

2012-08-01

Mean-deviation analysis, along with the existing theories of coherent risk measures and dual utility, is examined in the context of the theory of choice under uncertainty, which studies rational preference relations for random outcomes based on different sets of axioms such as transitivity, monotonicity, continuity, etc. An axiomatic foundation of the theory of coherent risk measures is obtained as a relaxation of the axioms of the dual utility theory, and a further relaxation of the axioms are shown to lead to the mean-deviation analysis. Paradoxes arising from the sets of axioms corresponding to these theories and their possible resolutions are discussed, and application of the mean-deviation analysis to optimal risk sharing and portfolio selection in the context of rational choice is considered. © 2012 Society for Risk Analysis.

Interdependency between Risk Assessments for Self and Other in the Field of Comparative Optimism: The Contribution of Response Times

ERIC Educational Resources Information Center

Spitzenstetter, Florence; Schimchowitsch, Sarah

2012-01-01

By introducing a response-time measure in the field of comparative optimism, this study was designed to explore how people estimate risk to self and others depending on the evaluation order (self/other or other/self). Our results show the interdependency between self and other answers. Indeed, while response time for risk assessment for the self…

Heart attack risk perception biases among hypertension patients: the role of educational level and worry.

PubMed

Peterson, Laurel M; Helweg-Larsen, Marie; Volpp, Kevin G; Kimmel, Stephen E

2012-01-01

Risk biases such as comparative optimism (thinking one is better off than similar others) and risk inaccuracy (misestimating one's risk compared to one's calculated risk) for health outcomes are common. Little research has investigated racial or socioeconomic differences in these risk biases. Results from a survey of individuals with poorly controlled hypertension (N=813) indicated that participants showed (1) comparative optimism for heart attack risk by underestimating their heart attack risk compared to similar others, and (2) risk inaccuracy by overestimating their heart attack risk compared to their calculated heart attack risk. More highly educated participants were more comparatively optimistic because they rated their personal risk as lower; education was not related to risk inaccuracy. Neither race nor the federal poverty level was related to risk biases. Worry partially mediated the relationship between education and personal risk. Results are discussed as they relate to the existing literature on risk perception.

Timing of conception and the risk of spontaneous abortion among pregnancies occurring during the use of natural family planning.

PubMed

Gray, R H; Simpson, J L; Kambic, R T; Queenan, J T; Mena, P; Perez, A; Barbato, M

1995-05-01

Our purpose was to ascertain the effects of timing of conception on the risk of spontaneous abortion. To assess these effects, women who conceived while using natural family planning were identified in five centers worldwide between 1987 and 1993. Timing of conception was determined from 868 natural family planning charts that recorded day of intercourse and indices of ovulation (cervical mucus peak obtained according to the ovulation method and/or basal body temperature). Conceptions on days - 1 or 0 with respect to the natural family planning estimated day of ovulation were considered to be "optimally timed," and all other conceptions were considered as "non-optimally timed." The rate of spontaneous abortions per 100 pregnancies was examined in relation to timing of conception, ages, reproductive history, and other covariates with bivariate and multivariate statistical methods. There were 88 spontaneous abortions among 868 pregnancies (10.1%). The spontaneous abortion rate was similar for 361 optimally timed conceptions (9.1%) and 507 non-optimally timed conceptions (10.9%). However, among 171 women who had experienced a spontaneous abortion in a prior pregnancy, the rate of spontaneous abortion in the index pregnancy was significantly higher with non-optimally timed conceptions (22.6%) as compared with optimally timed conceptions (7.3%). This association was not observed among 697 women with no history of pregnancy loss. The adjusted relative risk of spontaneous abortion among women with non-optimally timed conceptions and a history of pregnancy loss was 2.35 (95% confidence intervals 1.42 to 3.89). The excess risk of spontaneous abortion was observed with both preovulatory and postovulatory conceptions. Overall, there is no excess risk of spontaneous abortion among the pregnancies conceived during natural family planning use. However, among women with a history of pregnancy loss, there is an increased risk of spontaneous abortion associated with preovulatory or postovulatory delayed conceptions.

Assessing predation risk: optimal behaviour and rules of thumb.

PubMed

Welton, Nicky J; McNamara, John M; Houston, Alasdair I

2003-12-01

We look at a simple model in which an animal makes behavioural decisions over time in an environment in which all parameters are known to the animal except predation risk. In the model there is a trade-off between gaining information about predation risk and anti-predator behaviour. All predator attacks lead to death for the prey, so that the prey learns about predation risk by virtue of the fact that it is still alive. We show that it is not usually optimal to behave as if the current unbiased estimate of the predation risk is its true value. We consider two different ways to model reproduction; in the first scenario the animal reproduces throughout its life until it dies, and in the second scenario expected reproductive success depends on the level of energy reserves the animal has gained by some point in time. For both of these scenarios we find results on the form of the optimal strategy and give numerical examples which compare optimal behaviour with behaviour under simple rules of thumb. The numerical examples suggest that the value of the optimal strategy over the rules of thumb is greatest when there is little current information about predation risk, learning is not too costly in terms of predation, and it is energetically advantageous to learn about predation. We find that for the model and parameters investigated, a very simple rule of thumb such as 'use the best constant control' performs well.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugano, Yasutaka; Mizuta, Masahiro; Takao, Seishin

Purpose: Radiotherapy of solid tumors has been performed with various fractionation regimens such as multi- and hypofractionations. However, the ability to optimize the fractionation regimen considering the physical dose distribution remains insufficient. This study aims to optimize the fractionation regimen, in which the authors propose a graphical method for selecting the optimal number of fractions (n) and dose per fraction (d) based on dose–volume histograms for tumor and normal tissues of organs around the tumor. Methods: Modified linear-quadratic models were employed to estimate the radiation effects on the tumor and an organ at risk (OAR), where the repopulation of themore » tumor cells and the linearity of the dose-response curve in the high dose range of the surviving fraction were considered. The minimization problem for the damage effect on the OAR was solved under the constraint that the radiation effect on the tumor is fixed by a graphical method. Here, the damage effect on the OAR was estimated based on the dose–volume histogram. Results: It was found that the optimization of fractionation scheme incorporating the dose–volume histogram is possible by employing appropriate cell surviving models. The graphical method considering the repopulation of tumor cells and a rectilinear response in the high dose range enables them to derive the optimal number of fractions and dose per fraction. For example, in the treatment of prostate cancer, the optimal fractionation was suggested to lie in the range of 8–32 fractions with a daily dose of 2.2–6.3 Gy. Conclusions: It is possible to optimize the number of fractions and dose per fraction based on the physical dose distribution (i.e., dose–volume histogram) by the graphical method considering the effects on tumor and OARs around the tumor. This method may stipulate a new guideline to optimize the fractionation regimen for physics-guided fractionation.« less

Guaranteed epsilon-optimal treatment plans with the minimum number of beams for stereotactic body radiation therapy

NASA Astrophysics Data System (ADS)

Yarmand, Hamed; Winey, Brian; Craft, David

2013-09-01

Stereotactic body radiation therapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam’s-eye-view) known as ‘apertures’. Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan as the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined maximum deviation from the ideal plan is guaranteed). Since the treatment plan optimization is inherently a multi-criteria-optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon-optimality. We use mixed integer programming (MIP) for optimization. To reduce the computation time for the resultant MIP, we use two heuristics: a beam elimination scheme and a family of heuristic cuts, known as ‘neighbor cuts’, based on the concept of ‘adjacent beams’. We show the effectiveness of the proposed technique on two clinical cases, a liver and a lung case. Based on our technique we propose an algorithm for fast generation of epsilon-optimal plans.

Implementation of equity in resource allocation for regional earthquake risk mitigation using two-stage stochastic programming.

PubMed

Zolfaghari, Mohammad R; Peyghaleh, Elnaz

2015-03-01

This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two-stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user-defined level to achieve the equity-efficiency tradeoff in the decision-making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk-return tradeoff, equity-reconstruction expenditures tradeoff, and variation of per-capita expected earthquake loss in different income classes are also presented. © 2015 Society for Risk Analysis.

Single line source with and without vaginal loading and the impact on target coverage and organ at risk doses for cervix cancer Stages IB, II, and IIIB: treatment planning simulation in patients treated with MRI-guided adaptive brachytherapy in a multicentre study (EMBRACE).

PubMed

Nkiwane, Karen S; Pötter, Richard; Tanderup, Kari; Federico, Mario; Lindegaard, Jacob C; Kirisits, Christian

2013-01-01

Three-dimensional evaluation and comparison of target and organs at risk (OARs) doses from two traditional standard source loading patterns in the frame of MRI-guided cervical cancer brachytherapy for various clinical scenarios based on patient data collected in a multicenter trial setting. Two nonoptimized three-dimensional MRI-based treatment plans, Plan 1 (tandem and vaginal loading) and Plan 2 (tandem loading only), were generated for 134 patients from seven centers participating in the EMBRACE study. Both plans were normalized to point A (Pt. A). Target and OAR doses were evaluated in terms of minimum dose to 90% of the high-risk clinical target volume (HRCTV D90) grouped by tumor stage and minimum dose to the most exposed 2cm³ of the OARs volume. An HRCTV D90 ≥ Pt. A was achieved in 82% and 44% of the patients with Plans 1 and 2, respectively. Median HRCTV D90 with Plans 1 and 2 was 120% and 90% of Pt. A dose, respectively. Both plans had optimal dose coverage in 88% of Stage IB tumors; however, the tandem-only plan resulted in about 50% of dose reduction to the vagina and rectum. For Stages IIB and IIIB, Plan 1 had on average 35% better target coverage but with significant doses to OARs. Standard tandem loading alone results in good target coverage in most Stage IB tumors without violating OAR dose constraints. For Stage IIB tumors, standard vaginal loading improves the therapeutic window, however needs optimization to fulfill the dose prescription for target and OAR. In Stage IIIB, even optimized vaginal loading often does not fulfill the needs for dose prescription. The significant dose variation across various clinical scenarios for both target and OARs indicates the need for image-guided brachytherapy for optimal dose adaptation both for limited and advanced diseases. Copyright © 2013 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Developing Autism Screening Criteria for the Brief Infant Toddler Social Emotional Assessment (BITSEA)

ERIC Educational Resources Information Center

Giserman Kiss, Ivy; Feldman, Melanie S.; Sheldrick, R. Christopher; Carter, Alice S.

2017-01-01

There is a critical need for evidence-based, broadband behavioral, and ASD screening measures for use in pediatric and early educational settings to ensure that young children at risk for developing social-emotional disorders and/or ASD are provided with early intervention services to optimize long-term outcomes. The BITSEA is a 42-item screener…

Optimal house elevation for reducing flood-related losses

NASA Astrophysics Data System (ADS)

Xian, Siyuan; Lin, Ning; Kunreuther, Howard

2017-05-01

FEMA recommends that houses in coastal flood zones be elevated to at least 1 foot above the base flood elevation (BFE). However, this guideline is not specific and ignores characteristics of houses that affect their vulnerability. An economically optimal elevation level (OEL) is proposed that minimizes the combined cost of elevation and cumulative insurance premiums over the lifespan of the house. As an illustration, analysis is performed for various coastal houses in Ortley Beach, NJ. Compared with the strategy of raising houses to 1 foot above BFE, the strategy of raising houses to their OELs is much more economical for the homeowners. Elevating to the OELs also significantly reduces government spending on subsidizing low-income homeowners through, for example, a voucher program, to mitigate flood risk. These results suggest that policy makers should consider vulnerability factors in developing risk-reduction strategies. FEMA may recommend OELs to homeowners based on their flood hazards as well as house characteristics or at least providing more information and tools to homeowners to assist them in making more economical decisions. The OEL strategy can also be coupled with a voucher program to make the program more cost-effective.

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

News of Biomedical Advances in HIV: Relationship to Treatment Optimism and Expected Risk Behavior in US MSM.

PubMed

Zimmerman, Rick S; Kirschbaum, Allison L

2018-02-01

HIV treatment optimism and the ways in which news of HIV biomedical advances in HIV is presented to the most at-risk communities interact in ways that affect risk behavior and the incidence of HIV. The goal of the current study was to understand the relationships among HIV treatment optimism, knowledge of HIV biomedical advances, and current and expected increased risk behavior as a result of reading hypothetical news stories of further advances. Most of an online-recruited sample of MSM were quite knowledgeable about current biomedical advances. After reading three hypothetical news stories, 15-24% of those not living with HIV and 26-52% of those living with HIV reported their condom use would decrease if the story they read were true. Results suggest the importance of more cautious reporting on HIV biomedical advances, and for targeting individuals with greater treatment optimism and those living with HIV via organizations where they are most likely to receive their information about HIV.

Personality traits associated with genetic counselor compassion fatigue: the roles of dispositional optimism and locus of control.

PubMed

Injeyan, Marie C; Shuman, Cheryl; Shugar, Andrea; Chitayat, David; Atenafu, Eshetu G; Kaiser, Amy

2011-10-01

Compassion fatigue (CMF) arises as a consequence of secondary exposure to distress and can be elevated in some health practitioners. Locus of control and dispositional optimism are aspects of personality known to influence coping style. To investigate whether these personality traits influence CMF risk, we surveyed 355 genetic counselors about their CMF, locus of control orientation, and degree of dispositional optimism. Approximately half of respondents reported they experience CMF; 26.6% had considered leaving their job due to CMF symptoms. Mixed-method analyses revealed that genetic counselors having an external locus of control and low optimism were at highest risk for CMF. Those at highest risk experienced moderate-to-high burnout, low-to-moderate compassion satisfaction, and tended to rely on religion/spirituality when coping with stress. CMF risk was not influenced by years in practice, number of genetic counselor colleagues in the workplace, or completion of graduate training in this area. Recommendations for practice and education are outlined.

Risk Decision Making Model for Reservoir Floodwater resources Utilization

NASA Astrophysics Data System (ADS)

Huang, X.

2017-12-01

Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

Doing our best: optimization and the management of risk.

PubMed

Ben-Haim, Yakov

2012-08-01

Tools and concepts of optimization are widespread in decision-making, design, and planning. There is a moral imperative to "do our best." Optimization underlies theories in physics and biology, and economic theories often presume that economic agents are optimizers. We argue that in decisions under uncertainty, what should be optimized is robustness rather than performance. We discuss the equity premium puzzle from financial economics, and explain that the puzzle can be resolved by using the strategy of satisficing rather than optimizing. We discuss design of critical technological infrastructure, showing that satisficing of performance requirements--rather than optimizing them--is a preferable design concept. We explore the need for disaster recovery capability and its methodological dilemma. The disparate domains--economics and engineering--illuminate different aspects of the challenge of uncertainty and of the significance of robust-satisficing. © 2012 Society for Risk Analysis.

Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

NASA Astrophysics Data System (ADS)

Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra

2017-06-01

In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

Discovery of AZD2716: A Novel Secreted Phospholipase A2 (sPLA2) Inhibitor for the Treatment of Coronary Artery Disease

PubMed Central

2016-01-01

Expedited structure-based optimization of the initial fragment hit 1 led to the design of (R)-7 (AZD2716) a novel, potent secreted phospholipase A2 (sPLA2) inhibitor with excellent preclinical pharmacokinetic properties across species, clear in vivo efficacy, and minimized safety risk. Based on accumulated profiling data, (R)-7 was selected as a clinical candidate for the treatment of coronary artery disease. PMID:27774123

Optimizing Caffeine Use and Risk of Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review, Meta-analysis, and Application of Grading of Recommendations Assessment, Development, and Evaluation Methodology.

PubMed

Pakvasa, Mitali Atul; Saroha, Vivek; Patel, Ravi Mangal

2018-06-01

Caffeine reduces the risk of bronchopulmonary dysplasia (BPD). Optimizing caffeine use could increase therapeutic benefit. We performed a systematic-review and random-effects meta-analysis of studies comparing different timing of initiation and dose of caffeine on the risk of BPD. Earlier initiation, compared to later, was associated with a decreased risk of BPD (5 observational studies; n = 63,049, adjusted OR 0.69; 95% CI 0.64-0.75, GRADE: low quality). High-dose caffeine, compared to standard-dose, was associated with a decreased risk of BPD (3 randomized trials, n = 432, OR 0.65; 95% CI 0.43-0.97; GRADE: low quality). Higher quality evidence is needed to guide optimal caffeine use. Copyright © 2018 Elsevier Inc. All rights reserved.

On portfolio risk diversification

NASA Astrophysics Data System (ADS)

Takada, Hellinton H.; Stern, Julio M.

2017-06-01

The first portfolio risk diversification strategy was put into practice by the All Weather fund in 1996. The idea of risk diversification is related to the risk contribution of each available asset class or investment factor to the total portfolio risk. The maximum diversification or the risk parity allocation is achieved when the set of risk contributions is given by a uniform distribution. Meucci (2009) introduced the maximization of the Rényi entropy as part of a leverage constrained optimization problem to achieve such diversified risk contributions when dealing with uncorrelated investment factors. A generalization of the risk parity is the risk budgeting when there is a prior for the distribution of the risk contributions. Our contribution is the generalization of the existent optimization frameworks to be able to solve the risk budgeting problem. In addition, our framework does not possess any leverage constraint.

Simplify to survive: prescriptive layouts ensure profitable scaling to 32nm and beyond

NASA Astrophysics Data System (ADS)

Liebmann, Lars; Pileggi, Larry; Hibbeler, Jason; Rovner, Vyacheslav; Jhaveri, Tejas; Northrop, Greg

2009-03-01

The time-to-market driven need to maintain concurrent process-design co-development, even in spite of discontinuous patterning, process, and device innovation is reiterated. The escalating design rule complexity resulting from increasing layout sensitivities in physical and electrical yield and the resulting risk to profitable technology scaling is reviewed. Shortcomings in traditional Design for Manufacturability (DfM) solutions are identified and contrasted to the highly successful integrated design-technology co-optimization used for SRAM and other memory arrays. The feasibility of extending memory-style design-technology co-optimization, based on a highly simplified layout environment, to logic chips is demonstrated. Layout density benefits, modeled patterning and electrical yield improvements, as well as substantially improved layout simplicity are quantified in a conventional versus template-based design comparison on a 65nm IBM PowerPC 405 microprocessor core. The adaptability of this highly regularized template-based design solution to different yield concerns and design styles is shown in the extension of this work to 32nm with an increased focus on interconnect redundancy. In closing, the work not covered in this paper, focused on the process side of the integrated process-design co-optimization, is introduced.

Probabilistic Design of a Plate-Like Wing to Meet Flutter and Strength Requirements

NASA Technical Reports Server (NTRS)

Stroud, W. Jefferson; Krishnamurthy, T.; Mason, Brian H.; Smith, Steven A.; Naser, Ahmad S.

2002-01-01

An approach is presented for carrying out reliability-based design of a metallic, plate-like wing to meet strength and flutter requirements that are given in terms of risk/reliability. The design problem is to determine the thickness distribution such that wing weight is a minimum and the probability of failure is less than a specified value. Failure is assumed to occur if either the flutter speed is less than a specified allowable or the stress caused by a pressure loading is greater than a specified allowable. Four uncertain quantities are considered: wing thickness, calculated flutter speed, allowable stress, and magnitude of a uniform pressure load. The reliability-based design optimization approach described herein starts with a design obtained using conventional deterministic design optimization with margins on the allowables. Reliability is calculated using Monte Carlo simulation with response surfaces that provide values of stresses and flutter speed. During the reliability-based design optimization, the response surfaces and move limits are coordinated to ensure accuracy of the response surfaces. Studies carried out in the paper show the relationship between reliability and weight and indicate that, for the design problem considered, increases in reliability can be obtained with modest increases in weight.

Risk-Sensitivity in Sensorimotor Control

PubMed Central

Braun, Daniel A.; Nagengast, Arne J.; Wolpert, Daniel M.

2011-01-01

Recent advances in theoretical neuroscience suggest that motor control can be considered as a continuous decision-making process in which uncertainty plays a key role. Decision-makers can be risk-sensitive with respect to this uncertainty in that they may not only consider the average payoff of an outcome, but also consider the variability of the payoffs. Although such risk-sensitivity is a well-established phenomenon in psychology and economics, it has been much less studied in motor control. In fact, leading theories of motor control, such as optimal feedback control, assume that motor behaviors can be explained as the optimization of a given expected payoff or cost. Here we review evidence that humans exhibit risk-sensitivity in their motor behaviors, thereby demonstrating sensitivity to the variability of “motor costs.” Furthermore, we discuss how risk-sensitivity can be incorporated into optimal feedback control models of motor control. We conclude that risk-sensitivity is an important concept in understanding individual motor behavior under uncertainty. PMID:21283556

Evidence-Based Evaluation of Inferior Vena Cava Filter Complications Based on Filter Type

PubMed Central

Deso, Steven E.; Idakoji, Ibrahim A.; Kuo, William T.

2016-01-01

Many inferior vena cava (IVC) filter types, along with their specific risks and complications, are not recognized. The purpose of this study was to evaluate the various FDA-approved IVC filter types to determine device-specific risks, as a way to help identify patients who may benefit from ongoing follow-up versus prompt filter retrieval. An evidence-based electronic search (FDA Premarket Notification, MEDLINE, FDA MAUDE) was performed to identify all IVC filter types and device-specific complications from 1980 to 2014. Twenty-three IVC filter types (14 retrievable, 9 permanent) were identified. The devices were categorized as follows: conical (n = 14), conical with umbrella (n = 1), conical with cylindrical element (n = 2), biconical with cylindrical element (n = 2), helical (n = 1), spiral (n = 1), and complex (n = 1). Purely conical filters were associated with the highest reported risks of penetration (90–100%). Filters with cylindrical or umbrella elements were associated with the highest reported risk of IVC thrombosis (30–50%). Conical Bard filters were associated with the highest reported risks of fracture (40%). The various FDA-approved IVC filter types were evaluated for device-specific complications based on best current evidence. This information can be used to guide and optimize clinical management in patients with indwelling IVC filters. PMID:27247477

Using technology to assess and intervene with illicit drug-using persons at risk for HIV.

PubMed

Horvath, Keith J; Lammert, Sara; LeGrand, Sara; Muessig, Kathryn E; Bauermeister, José A

2017-09-01

This review describes recent literature on novel ways technology is used for assessment of illicit drug use and HIV risk behaviours, suggestions for optimizing intervention acceptability, and recently completed and ongoing technology-based interventions for drug-using persons at risk for HIV and others with high rates of drug use and HIV risk behaviour. Among studies (n = 5) comparing technology-based to traditional assessment methods, those using Ecological Momentary Assessment (EMA) had high rates of reported drug use and high concordance with traditional assessment methods. The two recent studies assessing the acceptability of mHealth approaches overall demonstrate high interest in these approaches. Current or in-progress technology-based interventions (n = 8) are delivered using mobile apps (n = 5), text messaging (n = 2) and computers (n = 1). Most intervention studies are in progress or do not report intervention outcomes; the results from one efficacy trial showed significantly higher HIV testing rates among persons in need of drug treatment. Studies are needed to continually assess technology adoption and intervention preferences among drug-using populations to ensure that interventions are appropriately matched to users. Large-scale technology-based intervention trials to assess the efficacy of these approaches, as well as the impact of individual intervention components, on drug use and other high-risk behaviours are recommended.

Optimization Under Uncertainty of Site-Specific Turbine Configurations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quick, J.; Dykes, K.; Graf, P.

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. Lastly, if there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtainedmore » with increasing risk aversion on the part of the designer.« less

Optimization under Uncertainty of Site-Specific Turbine Configurations: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quick, Julian; Dykes, Katherine; Graf, Peter

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained withmore » increasing risk aversion on the part of the designer.« less

Optimization Under Uncertainty of Site-Specific Turbine Configurations

DOE PAGES

Quick, J.; Dykes, K.; Graf, P.; ...

2016-10-03

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. Lastly, if there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtainedmore » with increasing risk aversion on the part of the designer.« less

The Apollo Capsule Optimization for Improved Stability and Computational/Experimental Data Comparisons

NASA Technical Reports Server (NTRS)

Cliff, Susan E.; Thomas, Scott D.

2005-01-01

Numerical optimization was employed on the Apollo Command Module to modify its external shape. The Apollo Command Module (CM) that was used on all NASA human space flights during the Apollo Space Program is stable and trimmed in an apex forward (alpha of approximately 40 to 80 degrees) position. This poses a safety risk if the CM separates from the launch tower during abort. Optimization was employed on the Apollo CM to remedy the undesirable stability characteristics of the configuration. Geometric shape changes were limited to axisymmetric modifications that altered the radius of the apex (R(sub A)), base radius (R(sub O)), corner radius (R(sub C)), and the cone half angle (theta), while the maximum diameter of the CM was held constant. The results of multipoint optimization on the CM indicated that the cross-range performance can be improved while maintaining robust apex-aft stability with a single trim point. Navier-Stokes computations were performed on the baseline and optimized configurations and confirmed the Euler-based optimization results. Euler Analysis of ten alternative CM vehicles with different values of the above four parameters are compared with the published experimental results of numerous wind tunnel tests during the late 1960's. These comparisons cover a wide Mach number range and a full 180-degree pitch range and show that the Euler methods are capable of fairly accurate force and moment computations and can separate the vehicle characteristics of these ten alternative configurations.

[Ecological risk assessment of typical karst basin based on land use change: A case study of Lijiang River basin, Southern China].

PubMed

Hu, Jin Long; Zhou, Zhi Xiang; Teng, Ming Jun; Luo, Nan

2017-06-18

Taking Lijiang River basin as study area, and based on the remote sensing images of 1973, 1986, 2000 and 2013, the land-use data were extracted, the ecological risk index was constructed, and the characteristics of spatiotemporal variation of ecological risk were analyzed by "3S" technique. The results showed that land use structure of Lijiang River basin was under relatively reasonable state and it was constantly optimizing during 1973-2013. Overall, the ecological risk of Lijiang River basin was maintained at a low level. Lowest and lower ecological risk region was dominant in Lijiang River basin, but the area of highest ecological risk expanded quickly. The spatial distribution of ecological risk was basically stable and showed an obvious ring structure, which gra-dually decreased from the axis of Xingan County Town-Lingchuan County Town-Guilin City-Yangshuo County Town to other regions. Region with lowest ecological risk mainly distributed in natural mountain forest area of the north and mid-eastern parts of Lijiang River basin, and region with highe-st ecological risk concentrated in Guilin City. The ecological risk distribution of Lijiang River basin presented significant slope and altitude differences, and it decreased with increasing slope and altitude. During the study period, the area of low ecological risk converted to high ecological risk gra-dually decreased and vice versa. On the whole, the ecological risk tended to decline rapidly in the Lijiang River basin.

Risk factors for the treatment outcome of retreated pulmonary tuberculosis patients in China: an optimized prediction model.

PubMed

Wang, X-M; Yin, S-H; Du, J; Du, M-L; Wang, P-Y; Wu, J; Horbinski, C M; Wu, M-J; Zheng, H-Q; Xu, X-Q; Shu, W; Zhang, Y-J

2017-07-01

Retreatment of tuberculosis (TB) often fails in China, yet the risk factors associated with the failure remain unclear. To identify risk factors for the treatment failure of retreated pulmonary tuberculosis (PTB) patients, we analyzed the data of 395 retreated PTB patients who received retreatment between July 2009 and July 2011 in China. PTB patients were categorized into 'success' and 'failure' groups by their treatment outcome. Univariable and multivariable logistic regression were used to evaluate the association between treatment outcome and socio-demographic as well as clinical factors. We also created an optimized risk score model to evaluate the predictive values of these risk factors on treatment failure. Of 395 patients, 99 (25·1%) were diagnosed as retreatment failure. Our results showed that risk factors associated with treatment failure included drug resistance, low education level, low body mass index (6 months), standard treatment regimen, retreatment type, positive culture result after 2 months of treatment, and the place where the first medicine was taken. An Optimized Framingham risk model was then used to calculate the risk scores of these factors. Place where first medicine was taken (temporary living places) received a score of 6, which was highest among all the factors. The predicted probability of treatment failure increases as risk score increases. Ten out of 359 patients had a risk score >9, which corresponded to an estimated probability of treatment failure >70%. In conclusion, we have identified multiple clinical and socio-demographic factors that are associated with treatment failure of retreated PTB patients. We also created an optimized risk score model that was effective in predicting the retreatment failure. These results provide novel insights for the prognosis and improvement of treatment for retreated PTB patients.

Optimizing spacecraft design - optimization engine development : progress and plans

NASA Technical Reports Server (NTRS)

Cornford, Steven L.; Feather, Martin S.; Dunphy, Julia R; Salcedo, Jose; Menzies, Tim

2003-01-01

At JPL and NASA, a process has been developed to perform life cycle risk management. This process requires users to identify: goals and objectives to be achieved (and their relative priorities), the various risks to achieving those goals and objectives, and options for risk mitigation (prevention, detection ahead of time, and alleviation). Risks are broadly defined to include the risk of failing to design a system with adequate performance, compatibility and robustness in addition to more traditional implementation and operational risks. The options for mitigating these different kinds of risks can include architectural and design choices, technology plans and technology back-up options, test-bed and simulation options, engineering models and hardware/software development techniques and other more traditional risk reduction techniques.

Portfolio Purchasing Decision for Mobile Power Equipment of B2C E-Commerce Export Retailer Based on CVaR

NASA Astrophysics Data System (ADS)

Yanchun, Wan; Qiucen, Chen

2017-11-01

Purchasing is an important part of export e-commerce of B2C, which plays an important role on risk and cost control in supply management. From the perspective of risk control, the paper construct a CVaR model for portfolio purchase. We select a heavy sales mobile power equipment from a typical B2C e-commerce export retailer as study sample. This study optimizes the purchasing strategy of this type of mobile power equipment. The research has some reference for similar enterprises in purchasing portfolio decision.

Optimal Predator Risk Assessment by the Sonar-Jamming Arctiine Moth Bertholdia trigona

PubMed Central

Corcoran, Aaron J.; Wagner, Ryan D.; Conner, William E.

2013-01-01

Nearly all animals face a tradeoff between seeking food and mates and avoiding predation. Optimal escape theory holds that an animal confronted with a predator should only flee when benefits of flight (increased survival) outweigh the costs (energetic costs, lost foraging time, etc.). We propose a model for prey risk assessment based on the predator's stage of attack. Risk level should increase rapidly from when the predator detects the prey to when it commits to the attack. We tested this hypothesis using a predator – the echolocating bat – whose active biosonar reveals its stage of attack. We used a prey defense – clicking used for sonar jamming by the tiger moth Bertholdia trigona– that can be readily studied in the field and laboratory and is enacted simultaneously with evasive flight. We predicted that prey employ defenses soon after being detected and targeted, and that prey defensive thresholds discriminate between legitimate predatory threats and false threats where a nearby prey is attacked. Laboratory and field experiments using playbacks of ultrasound signals and naturally behaving bats, respectively, confirmed our predictions. Moths clicked soon after bats detected and targeted them. Also, B. trigona clicking thresholds closely matched predicted optimal thresholds for discriminating legitimate and false predator threats for bats using search and approach phase echolocation – the period when bats are searching for and assessing prey. To our knowledge, this is the first quantitative study to correlate the sensory stimuli that trigger defensive behaviors with measurements of signals provided by predators during natural attacks in the field. We propose theoretical models for explaining prey risk assessment depending on the availability of cues that reveal a predator's stage of attack. PMID:23671686

HIV Treatment and Prevention: A Simple Model to Determine Optimal Investment.

PubMed

Juusola, Jessie L; Brandeau, Margaret L

2016-04-01

To create a simple model to help public health decision makers determine how to best invest limited resources in HIV treatment scale-up and prevention. A linear model was developed for determining the optimal mix of investment in HIV treatment and prevention, given a fixed budget. The model incorporates estimates of secondary health benefits accruing from HIV treatment and prevention and allows for diseconomies of scale in program costs and subadditive benefits from concurrent program implementation. Data sources were published literature. The target population was individuals infected with HIV or at risk of acquiring it. Illustrative examples of interventions include preexposure prophylaxis (PrEP), community-based education (CBE), and antiretroviral therapy (ART) for men who have sex with men (MSM) in the US. Outcome measures were incremental cost, quality-adjusted life-years gained, and HIV infections averted. Base case analysis indicated that it is optimal to invest in ART before PrEP and to invest in CBE before scaling up ART. Diseconomies of scale reduced the optimal investment level. Subadditivity of benefits did not affect the optimal allocation for relatively low implementation levels. The sensitivity analysis indicated that investment in ART before PrEP was optimal in all scenarios tested. Investment in ART before CBE became optimal when CBE reduced risky behavior by 4% or less. Limitations of the study are that dynamic effects are approximated with a static model. Our model provides a simple yet accurate means of determining optimal investment in HIV prevention and treatment. For MSM in the US, HIV control funds should be prioritized on inexpensive, effective programs like CBE, then on ART scale-up, with only minimal investment in PrEP. © The Author(s) 2015.

Matching Judicial Supervision to Clients’ Risk Status in Drug Court

PubMed Central

Marlowe, Douglas B.; Festinger, David S.; Lee, Patricia A.; Dugosh, Karen L.; Benasutti, Kathleen M.

2007-01-01

This article reports outcomes from a program of experimental research evaluating the risk principle in drug courts. Prior studies revealed that participants who were high risk and had (a) antisocial personality disorder or (b) a prior history of drug abuse treatment performed better in drug court when scheduled to attend biweekly judicial status hearings in court. In contrast, participants who were low risk performed equivalently regardless of the court hearings schedule. This study prospectively matches drug court clients to the optimal schedule of court hearings based on an assessment of their risk status and compares outcomes to clients randomly assigned to the standard hearings schedule. Results confirmed that participants who were high risk and matched to biweekly hearings had better during-treatment outcomes than participants assigned to status hearings as usual. These findings provide confirmation of the risk principle in drug courts and yield practical information for enhancing the efficacy and cost-efficiency of drug courts. PMID:18174915

Relationship of optimism and suicidal ideation in three groups of patients at varying levels of suicide risk.

PubMed

Huffman, Jeff C; Boehm, Julia K; Beach, Scott R; Beale, Eleanor E; DuBois, Christina M; Healy, Brian C

2016-06-01

Optimism has been associated with reduced suicidal ideation, but there have been few studies in patients at high suicide risk. We analyzed data from three study populations (total N = 319) with elevated risk of suicide: (1) patients with a recent acute cardiovascular event, (2) patients hospitalized for heart disease who had depression or an anxiety disorder, and (3) patients psychiatrically hospitalized for suicidal ideation or following a suicide attempt. For each study we analyzed the association between optimism (measured by the Life-Orientation Test-Revised) and suicidal ideation, and then completed an exploratory random effects meta-analysis of the findings to synthesize this data. The meta-analysis of the three studies showed that higher levels of self-reported optimism were associated with a lower likelihood of suicidal ideation (odds ratio [OR] = .89, 95% confidence interval [CI] = .85-.95, z = 3.94, p < .001), independent of age, gender, and depressive symptoms. This association held when using the subscales of the Life Orientation Test-Revised scale that measured higher optimism (OR = .84, 95% CI = .76-.92, z = 3.57, p < .001) and lower pessimism (OR = .83, 95% CI = .75-.92], z = 3.61, p < .001). These results also held when suicidal ideation was analyzed as an ordinal variable. Our findings suggest that optimism may be associated with a lower risk of suicidal ideation, above and beyond the effects of depressive symptoms, for a wide range of patients with clinical conditions that place them at elevated risk for suicide. Copyright © 2016 Elsevier Ltd. All rights reserved.

Relationship of optimism and suicidal ideation in three groups of patients at varying levels of suicide risk

PubMed Central

Huffman, Jeff C.; Boehm, Julia K.; Beach, Scott R.; Beale, Eleanor E.; DuBois, Christina M.; Healy, Brian C.

2016-01-01

Optimism has been associated with reduced suicidal ideation, but there have been few studies in patients at high suicide risk. We analyzed data from three study populations (total N=319) with elevated risk of suicide: (1) patients with a recent acute cardiovascular event, (2) patients hospitalized for heart disease who had depression or an anxiety disorder, and (3) patients psychiatrically hospitalized for suicidal ideation or following a suicide attempt. For each study we analyzed the association between optimism (measured by the Life-Orientation Test-Revised) and suicidal ideation, and then completed an exploratory random effects meta-analysis of the findings to synthesize this data. The meta-analysis of the three studies showed that higher levels of self-reported optimism were associated with a lower likelihood of suicidal ideation (odds ratio [OR]=.89, 95% confidence interval [CI]=.85–.95, z=3.94, p<.001), independent of age, gender, and depressive symptoms. This association held when using the subscales of the Life Orientation Test-Revised scale that measured higher optimism (OR=.84, 95% CI=.76–.92, z=3.57, p<.001) and lower pessimism (OR=.83, 95% CI= .75–.92], z=3.61, p<.001). These results also held when suicidal ideation was analyzed as an ordinal variable. Our findings suggest that optimism may be associated with a lower risk of suicidal ideation, above and beyond the effects of depressive symptoms, for a wide range of patients with clinical conditions that place them at elevated risk for suicide. PMID:26994340

Optimal helicopter trajectory planning for terrain following flight

NASA Technical Reports Server (NTRS)

Menon, P. K. A.

1990-01-01

Helicopters operating in high threat areas have to fly close to the earth surface to minimize the risk of being detected by the adversaries. Techniques are presented for low altitude helicopter trajectory planning. These methods are based on optimal control theory and appear to be implementable onboard in realtime. Second order necessary conditions are obtained to provide a criterion for finding the optimal trajectory when more than one extremal passes through a given point. A second trajectory planning method incorporating a quadratic performance index is also discussed. Trajectory planning problem is formulated as a differential game. The objective is to synthesize optimal trajectories in the presence of an actively maneuvering adversary. Numerical methods for obtaining solutions to these problems are outlined. As an alternative to numerical method, feedback linearizing transformations are combined with the linear quadratic game results to synthesize explicit nonlinear feedback strategies for helicopter pursuit-evasion. Some of the trajectories generated from this research are evaluated on a six-degree-of-freedom helicopter simulation incorporating an advanced autopilot. The optimal trajectory planning methods presented are also useful for autonomous land vehicle guidance.

Determinants of blood pressure control amongst hypertensive patients in Northwest Ethiopia.

PubMed

Teshome, Destaw Fetene; Demssie, Amsalu Feleke; Zeleke, Berihun Megabiaw

2018-01-01

Controlling blood pressure (BP) leads to significant reduction in cardiovascular risks and associated deaths. In Ethiopia, data is scarce about the level and determinants of optimal BP control among hypertensive patients. This study aimed to assess the prevalence and associated factors of optimal BP control among hypertensive patients attending at a district hospital. A hospital-based, cross-sectional study was conducted among 392 hypertensive patients who were on treatment and follow-up at a district hospital. A structured questionnaire adopted from WHO approach was prepared to collect the data. Medication adherence was measured by the four-item Morisky Green Levine Scale, with a score ≥3 defined as "good adherence". Blood pressure was measured, and optimal BP control was 0DEFined as systolic BP < 140 mmHg and diastolic BP<90 mmHg. Both binary and multivariable logistic regressions models were fitted to identify correlates of optimal BP control. All statistical tests were two-sided and a p values <0.05 was considered for statistical significance. The mean age of the participants was 58 years (SD±13 years). Over half (53.8%) were females. Three quarters (77.3%) of the participants were adherent to their medications. The overall proportion of participants with optimally controlled BP was 42.9%.Female sex (Adjusted Odd Ratio(AOR) = 1.94, 95% CI: 1.15, 3.26), age older than 60 years (AOR = 2.95, 95% CI: 1.18, 7.40), consumption of vegetables on most days of the week (AOR = 2.16, 95% CI: 1.25, 3.73), physical activity (AOR = 4.85, 95% CI: 2.39, 9.83), and taking less than three drugs per day (AOR = 3.04, 95% CI: 1.51, 6.14) were positively associated with optimally controlled BP. Poor adherence to medications (AOR = 0.18, 95% CI: 0.09, 0.35), having asthma comorbidity (AOR = 0.33, 95% CI:0.12, 0.88) and use of top added salt on a plate (AOR = 0.20, 95% CI:0.11, 0.36) were negatively associated with optimal BP control. A higher proportion of hypertensive patients remain with un-controlled BP. Modifiable risk factors including poor adherence to medications, lack of physical exercise, adding salt into meals, being on multiple medications and comorbidities were significantly and independently associated with poor BP control. Evidence-based, adherence-enhancing and healthy life style interventions should be implemented.

Minimax estimation of qubit states with Bures risk

NASA Astrophysics Data System (ADS)

Acharya, Anirudh; Guţă, Mădălin

2018-04-01

The central problem of quantum statistics is to devise measurement schemes for the estimation of an unknown state, given an ensemble of n independent identically prepared systems. For locally quadratic loss functions, the risk of standard procedures has the usual scaling of 1/n. However, it has been noticed that for fidelity based metrics such as the Bures distance, the risk of conventional (non-adaptive) qubit tomography schemes scales as 1/\\sqrt{n} for states close to the boundary of the Bloch sphere. Several proposed estimators appear to improve this scaling, and our goal is to analyse the problem from the perspective of the maximum risk over all states. We propose qubit estimation strategies based on separate adaptive measurements, and collective measurements, that achieve 1/n scalings for the maximum Bures risk. The estimator involving local measurements uses a fixed fraction of the available resource n to estimate the Bloch vector direction; the length of the Bloch vector is then estimated from the remaining copies by measuring in the estimator eigenbasis. The estimator based on collective measurements uses local asymptotic normality techniques which allows us to derive upper and lower bounds to its maximum Bures risk. We also discuss how to construct a minimax optimal estimator in this setup. Finally, we consider quantum relative entropy and show that the risk of the estimator based on collective measurements achieves a rate O(n-1log n) under this loss function. Furthermore, we show that no estimator can achieve faster rates, in particular the ‘standard’ rate n ‑1.

A quality by design approach to optimization of emulsions for electrospinning using factorial and D-optimal designs.

PubMed

Badawi, Mariam A; El-Khordagui, Labiba K

2014-07-16

Emulsion electrospinning is a multifactorial process used to generate nanofibers loaded with hydrophilic drugs or macromolecules for diverse biomedical applications. Emulsion electrospinnability is greatly impacted by the emulsion pharmaceutical attributes. The aim of this study was to apply a quality by design (QbD) approach based on design of experiments as a risk-based proactive approach to achieve predictable critical quality attributes (CQAs) in w/o emulsions for electrospinning. Polycaprolactone (PCL)-thickened w/o emulsions containing doxycycline HCl were formulated using a Span 60/sodium lauryl sulfate (SLS) emulsifier blend. The identified emulsion CQAs (stability, viscosity and conductivity) were linked with electrospinnability using a 3(3) factorial design to optimize emulsion composition for phase stability and a D-optimal design to optimize stable emulsions for viscosity and conductivity after shifting the design space. The three independent variables, emulsifier blend composition, organic:aqueous phase ratio and polymer concentration, had a significant effect (p<0.05) on emulsion CQAs, the emulsifier blend composition exerting prominent main and interaction effects. Scanning electron microscopy (SEM) of emulsion-electrospun NFs and desirability functions allowed modeling of emulsion CQAs to predict electrospinnable formulations. A QbD approach successfully built quality in electrospinnable emulsions, allowing development of hydrophilic drug-loaded nanofibers with desired morphological characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.

Subjective Invulnerability, Optimism Bias and Adjustment in Emerging Adulthood

ERIC Educational Resources Information Center

Lapsley, Daniel K.; Hill, Patrick L.

2010-01-01

The relationship between subjective invulnerability and optimism bias in risk appraisal, and their comparative association with indices of risk activity, substance use and college adjustment problems was assessed in a sample of 350 (M [subscript age] = 20.17; 73% female; 93% White/European American) emerging adults. Subjective invulnerability was…

Communication about family members' risk of melanoma: self-reported practices of dermatologists in the United States.

PubMed

Oliveria, Susan A; Heneghan, Maureen K; Halpern, Allan C; Hay, Jennifer L; Geller, Alan C

2012-05-01

To assess current self-reported communication and screening practices of dermatologists to their patients with melanoma about family members' risk of melanoma at the time of diagnosis and to understand the barriers that dermatologists encounter in communicating risk to patients. Descriptive survey study. Office-based practicing physicians in the United States. One thousand dermatologists. Melanoma risk communication practices. Of 974 eligible dermatologists, 406 completed the survey (response rate, 41.7%). Almost 85% of dermatologists reported that they often or always communicate risk to patients with melanoma about their first-degree relatives, and almost 80% reported that they often or always advise their patients with melanoma that their older children (18 years) may be at greater risk of skin cancer. However, less than 50% of dermatologists routinely offered to screen first-degree relatives who live nearby, while only 19.7% used medical record reminders to note communication of melanoma risk to family members. Most dermatologists reported no major barriers to melanoma risk communication. However, the presence of "any risk communication barrier" (time constraints, absence of guidelines, or lack of written material) was associated with reduced melanoma risk communication practices by dermatologists. The observed high rates of self-reported risk communication by dermatologists to patients with melanoma about their first-degree family members are encouraging. However, the reported low rates of actual screening of first-degree relatives warrant easy-to-administer office-based medical record reminders to facilitate and optimize screening of at-risk relatives.

A Longitudinal Examination of Hope and Optimism and Their Role in Type 1 Diabetes in Youths.

PubMed

Van Allen, Jason; Steele, Ric G; Nelson, Michael B; Peugh, James; Egan, Anna; Clements, Mark; Patton, Susana R

2016-08-01

To test the longitudinal associations between hope and optimism and health outcomes (i.e., HbA1c and self-monitored blood glucose [SMBG]) among youths with Type 1 diabetes mellitus (T1DM) over a 6-month period. A total of 110 participants (aged 10-16 years) completed study measures at Time 1, and 81 completed measures at Time 2. Analyses examined hope and optimism as predictors of change in health outcomes, and examined SMBG as a mediator of the relationship between hope and optimism, and HbA1c. Change in hope, but not optimism, was associated with change in SMBG and HbA1c. Change in SMBG mediated the relationship between change in hope and HbA1c, but not between optimism and HbA1c. It may be beneficial to assess hope in pediatric T1DM patients to identify youths who may be at risk for poor diabetes management, and to test the benefit of hope-based intervention efforts in clinical studies. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A scan statistic for identifying optimal risk windows in vaccine safety studies using self-controlled case series design.

PubMed

Xu, Stanley; Hambidge, Simon J; McClure, David L; Daley, Matthew F; Glanz, Jason M

2013-08-30

In the examination of the association between vaccines and rare adverse events after vaccination in postlicensure observational studies, it is challenging to define appropriate risk windows because prelicensure RCTs provide little insight on the timing of specific adverse events. Past vaccine safety studies have often used prespecified risk windows based on prior publications, biological understanding of the vaccine, and expert opinion. Recently, a data-driven approach was developed to identify appropriate risk windows for vaccine safety studies that use the self-controlled case series design. This approach employs both the maximum incidence rate ratio and the linear relation between the estimated incidence rate ratio and the inverse of average person time at risk, given a specified risk window. In this paper, we present a scan statistic that can identify appropriate risk windows in vaccine safety studies using the self-controlled case series design while taking into account the dependence of time intervals within an individual and while adjusting for time-varying covariates such as age and seasonality. This approach uses the maximum likelihood ratio test based on fixed-effects models, which has been used for analyzing data from self-controlled case series design in addition to conditional Poisson models. Copyright © 2013 John Wiley & Sons, Ltd.

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies.

PubMed

Paté-Cornell, M-Elisabeth; Kuypers, Marshall; Smith, Matthew; Keller, Philip

2018-02-01

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system-based for high-consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward-looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high-consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents. © 2017 Society for Risk Analysis.

Personal protective equipment and improving compliance among healthcare workers in high-risk settings.

PubMed

Honda, Hitoshi; Iwata, Kentaro

2016-08-01

Personal protective equipment (PPE) protects healthcare workers (HCWs) from infection by highly virulent pathogens via exposure to body fluids and respiratory droplets. Given the recent outbreaks of contagious infectious diseases worldwide, including Ebola virus and Middle Eastern respiratory syndrome, there is urgent need for further research to determine optimal PPE use in high-risk settings. This review intends to provide a general understanding of PPE and to provide guidelines for appropriate use based on current evidence. Although previous studies have focused on the efficacy of PPE in preventing transmission of pathogens, recent studies have examined the dangers to HCWs during removal of PPE when risk of contamination is highest. Access to adequate PPE supplies is crucial to preventing transmission of pathogens, especially in resource-limited settings. Adherence to appropriate PPE use is a challenge due to inadequate education on its usage, technical difficulties, and tolerability of PPE in the workplace. Future projects aim at ameliorating this situation, including redesigning PPE which is crucial to improving the safety of HCWs. PPE remains the most important strategy for protecting HCW from potentially fatal pathogens. Further research into optimal PPE design and use to improve the safety of HCWs is urgently needed.

Pregnancy with Portal Hypertension

PubMed Central

Aggarwal, Neelam; Negi, Neha; Aggarwal, Aakash; Bodh, Vijay; Dhiman, Radha K.

2014-01-01

Even though pregnancy is rare with cirrhosis and advanced liver disease, but it may co-exist in the setting of non-cirrhotic portal hypertension as liver function is preserved but whenever encountered together is a complex clinical dilemma. Pregnancy in a patient with portal hypertension presents a special challenge to the obstetrician as so-called physiological hemodynamic changes associated with pregnancy, needed for meeting demands of the growing fetus, worsen the portal hypertension thereby putting mother at risk of potentially life-threatening complications like variceal hemorrhage. Risks of variceal bleed and hepatic decompensation increase many fold during pregnancy. Optimal management revolves round managing the portal hypertension and its complications. Thus management of such cases requires multi-speciality approach involving obstetricians experienced in dealing with high risk cases, hepatologists, anesthetists and neonatologists. With advancement in medical field, pregnancy is not contra-indicated in these women, as was previously believed. This article focuses on the different aspects of pregnancy with portal hypertension with special emphasis on specific cause wise treatment options to decrease the variceal bleed and hepatic decompensation. Based on extensive review of literature, management from pre-conceptional period to postpartum is outlined in order to have optimal maternal and perinatal outcomes. PMID:25755552

A New Artificial Neural Network Enhanced by the Shuffled Complex Evolution Optimization with Principal Component Analysis (SP-UCI) for Water Resources Management

NASA Astrophysics Data System (ADS)

Hayatbini, N.; Faridzad, M.; Yang, T.; Akbari Asanjan, A.; Gao, X.; Sorooshian, S.

2016-12-01

The Artificial Neural Networks (ANNs) are useful in many fields, including water resources engineering and management. However, due to the non-linear and chaotic characteristics associated with natural processes and human decision making, the use of ANNs in real-world applications is still limited, and its performance needs to be further improved for a broader practical use. The commonly used Back-Propagation (BP) scheme and gradient-based optimization in training the ANNs have already found to be problematic in some cases. The BP scheme and gradient-based optimization methods are associated with the risk of premature convergence, stuck in local optimums, and the searching is highly dependent on initial conditions. Therefore, as an alternative to BP and gradient-based searching scheme, we propose an effective and efficient global searching method, termed the Shuffled Complex Evolutionary Global optimization algorithm with Principal Component Analysis (SP-UCI), to train the ANN connectivity weights. Large number of real-world datasets are tested with the SP-UCI-based ANN, as well as various popular Evolutionary Algorithms (EAs)-enhanced ANNs, i.e., Particle Swarm Optimization (PSO)-, Genetic Algorithm (GA)-, Simulated Annealing (SA)-, and Differential Evolution (DE)-enhanced ANNs. Results show that SP-UCI-enhanced ANN is generally superior over other EA-enhanced ANNs with regard to the convergence and computational performance. In addition, we carried out a case study for hydropower scheduling in the Trinity Lake in the western U.S. In this case study, multiple climate indices are used as predictors for the SP-UCI-enhanced ANN. The reservoir inflows and hydropower releases are predicted up to sub-seasonal to seasonal scale. Results show that SP-UCI-enhanced ANN is able to achieve better statistics than other EAs-based ANN, which implies the usefulness and powerfulness of proposed SP-UCI-enhanced ANN for reservoir operation, water resources engineering and management. The SP-UCI-enhanced ANN is universally applicable to many other regression and prediction problems, and it has a good potential to be an alternative to the classical BP scheme and gradient-based optimization methods.

A New Perspective on Modeling Groundwater-Driven Health Risk With Subjective Information

NASA Astrophysics Data System (ADS)

Ozbek, M. M.

2003-12-01

Fuzzy rule-based systems provide an efficient environment for the modeling of expert information in the context of risk management for groundwater contamination problems. In general, their use in the form of conditional pieces of knowledge, has been either as a tool for synthesizing control laws from data (i.e., conjunction-based models), or in a knowledge representation and reasoning perspective in Artificial Intelligence (i.e., implication-based models), where only the latter may lead to coherence problems (e.g., input data that leads to logical inconsistency when added to the knowledge base). We implement a two-fold extension to an implication-based groundwater risk model (Ozbek and Pinder, 2002) including: 1) the implementation of sufficient conditions for a coherent knowledge base, and 2) the interpolation of expert statements to supplement gaps in knowledge. The original model assumes statements of public health professionals for the characterization of the exposed individual and the relation of dose and pattern of exposure to its carcinogenic effects. We demonstrate the utility of the extended model in that it: 1)identifies inconsistent statements and establishes coherence in the knowledge base, and 2) minimizes the burden of knowledge elicitation from the experts for utilizing existing knowledge in an optimal fashion.ÿÿ

Discrete homotopy analysis for optimal trading execution with nonlinear transient market impact

NASA Astrophysics Data System (ADS)

Curato, Gianbiagio; Gatheral, Jim; Lillo, Fabrizio

2016-10-01

Optimal execution in financial markets is the problem of how to trade a large quantity of shares incrementally in time in order to minimize the expected cost. In this paper, we study the problem of the optimal execution in the presence of nonlinear transient market impact. Mathematically such problem is equivalent to solve a strongly nonlinear integral equation, which in our model is a weakly singular Urysohn equation of the first kind. We propose an approach based on Homotopy Analysis Method (HAM), whereby a well behaved initial trading strategy is continuously deformed to lower the expected execution cost. Specifically, we propose a discrete version of the HAM, i.e. the DHAM approach, in order to use the method when the integrals to compute have no closed form solution. We find that the optimal solution is front loaded for concave instantaneous impact even when the investor is risk neutral. More important we find that the expected cost of the DHAM strategy is significantly smaller than the cost of conventional strategies.

Simulation of a class of hazardous situations in the ICS «INM RAS - Baltic Sea»

NASA Astrophysics Data System (ADS)

Zakharova, Natalia; Agoshkov, Valery; Aseev, Nikita; Parmuzin, Eugene; Sheloput, Tateana; Shutyaev, Victor

2017-04-01

Development of Informational Computational Systems (ICS) for data assimilation procedures is one of multidisciplinary problems. To study and solve these problems one needs to apply modern results from different disciplines and recent developments in mathematical modeling, theory of adjoint equations and optimal control, inverse problems, numerical methods theory, numerical algebra, scientific computing and processing of satellite data. In this work the results on the ICS development for PC-ICS "INM RAS - Baltic Sea" are presented. We discuss practical problems studied by ICS. The System includes numerical model of the Baltic Sea thermodynamics, the new oil spill model describing the propagation of a slick at the Sea surface (Agoshkov, Aseev et al., 2014) and the optimal ship route calculating block (Agoshkov, Zayachkovsky et al., 2014). The ICS is based on the INMOM numerical model of the Baltic Sea thermodynamics (Zalesny et al., 2013). It is possible to calculate main hydrodynamic parameters (temperature, salinity, velocities, sea level) using user-friendly interface of the ICS. The System includes data assimilation procedures (Agoshkov, 2003, Parmuzin, Agoshkov, 2012) and one can use the block of variational assimilation of the sea surface temperature in order to obtain main hydrodynamic parameters. Main possibilities of the ICS and several numerical experiments are presented in the work. By the problem of risk control is meant a problem of determination of optimal resources quantity which are necessary for decreasing the risk to some acceptable value. Mass of oil slick is chosen as a function of control. For the realization of the random variable the quadratic "functional of cost" is introduced. It comprises cleaning costs and deviation of damage of oil pollution from its acceptable value. The problem of minimization of this functional is solved based on the methods of optimal control and the theory of adjoint equations. The solution of this problem is explicitly found. The study was supported by the Russian Foundation for Basic Research (project 16-31-00510) and by the Russian Science Foundation (project №14-11-00609). V. I. Agoshkov, Methods of Optimal Control and Adjoint Equations in Problems of Mathematical Physics. INM RAS, Moscow, 2003 (in Russian). V. B. Zalesny, A. V. Gusev, V. O. Ivchenko, R. Tamsalu, and R. Aps, Numerical model of the Baltic Sea circulation. Russ. J. Numer. Anal. Math. Modelling 28 (2013), No. 1, 85-100. V.I. Agoshkov, A.O. Zayachkovskiy, R. Aps, P. Kujala, and J. Rytkönen. Risk theory based solution to the problem of optimal vessel route // Russian Journal of Numerical Analysis and Mathematical Modelling. 2014. Volume 29, Issue 2, Pages 69-78. Agoshkov, V., Aseev, N., Aps, R., Kujala, P., Rytkönen, J., Zalesny, V. The problem of control of oil pollution risk in the Baltic Sea // Russian Journal of Numerical Analysis and Mathematical Modelling. 2014. Volume 29, Issue 2, Pages 93-105. E. I. Parmuzin and V. I. Agoshkov, Numerical solution of the variational assimilation problem for sea surface temperature in the model of the Black Sea dynamics. Russ. J. Numer. Anal. Math. Modelling 27 (2012), No. 1, 69-94. Olof Liungman and Johan Mattsson. Scientic Documentation of Seatrack Web; physical processes, algorithms and references, 2011.

Does unbelted safety requirement affect protection for belted occupants?

PubMed

Hu, Jingwen; Klinich, Kathleen D; Manary, Miriam A; Flannagan, Carol A C; Narayanaswamy, Prabha; Reed, Matthew P; Andreen, Margaret; Neal, Mark; Lin, Chin-Hsu

2017-05-29

Federal regulations in the United States require vehicles to meet occupant performance requirements with unbelted test dummies. Removing the test requirements with unbelted occupants might encourage the deployment of seat belt interlocks and allow restraint optimization to focus on belted occupants. The objective of this study is to compare the performance of restraint systems optimized for belted-only occupants with those optimized for both belted and unbelted occupants using computer simulations and field crash data analyses. In this study, 2 validated finite element (FE) vehicle/occupant models (a midsize sedan and a midsize SUV) were selected. Restraint design optimizations under standardized crash conditions (U.S.-NCAP and FMVSS 208) with and without unbelted requirements were conducted using Hybrid III (HIII) small female and midsize male anthropomorphic test devices (ATDs) in both vehicles on both driver and right front passenger positions. A total of 10 to 12 design parameters were varied in each optimization using a combination of response surface method (RSM) and genetic algorithm. To evaluate the field performance of restraints optimized with and without unbelted requirements, 55 frontal crash conditions covering a greater variety of crash types than those in the standardized crashes were selected. A total of 1,760 FE simulations were conducted for the field performance evaluation. Frontal crashes in the NASS-CDS database from 2002 to 2012 were used to develop injury risk curves and to provide the baseline performance of current restraint system and estimate the injury risk change by removing the unbelted requirement. Unbelted requirements do not affect the optimal seat belt and airbag design parameters in 3 out of 4 vehicle/occupant position conditions, except for the SUV passenger side. Overall, compared to the optimal designs with unbelted requirements, optimal designs without unbelted requirements generated the same or lower total injury risks for belted occupants depending on statistical methods used for the analysis, but they could also increase the total injury risks for unbelted occupants. This study demonstrated potential for reducing injury risks to belted occupants if the unbelted requirements are eliminated. Further investigations are necessary to confirm these findings.

Performance of a risk index for advanced proximal colorectal neoplasia among a racially/ethnically diverse patient population (risk index for advanced proximal neoplasia).

PubMed

Levitzky, Benjamin E; Brown, Colin C; Heeren, Timothy C; Schroy, Paul C

2011-06-01

Tailoring the use of screening colonoscopy based on the risk of advanced proximal neoplasia (APN) has been advocated as a strategy for reducing demand and optimizing effectiveness. A 7-point index based on age, sex, and distal findings at sigmoidoscopy has been proposed that stratifies individuals into low, intermediate, and high-risk categories. The aim of this cross-sectional analysis was to determine the validity of this index, which was originally derived and validated among mostly whites, for black and Hispanic patients. Data, including age, sex, colonoscopic findings, and pathology, were collected retrospectively from 1,481 white, 1,329 black, and 689 Hispanic asymptomatic, average-risk patients undergoing screening colonoscopy between 2000 and 2005. Cumulative scores ranging from 0 to 7 were derived for each subject and categorized as low, intermediate, or high risk. Rates of APN were assessed for each risk category after stratification by race/ethnicity. Index performance was assessed using the C-statistic and compared across the three racial groups. Rates of APN among patients categorized as low, intermediate, or high risk increased from 1.0 to 2.8 to 3.7% for whites, 1.0 to 2.2 to 4.2% for blacks, and 0.6 to 1.9 to 3.7% for Hispanics. The index performed similarly for all three groups, but showed limited ability to discriminate low from intermediate-risk patients, with C-statistic values of 0.62 for whites, 0.63 for blacks, and 0.68 for Hispanics. A risk index based on age, sex, and distal endoscopic findings has limited ability to discriminate low from intermediate-risk white, black, and Hispanic patients for APN.

Optimal cutoff of the waist-to-hip ratio for detecting cardiovascular risk factors among Han adults in Xinjiang.

PubMed

Li, Shuang-Shuang; Pan, Shuo; Ma, Yi-Tong; Yang, Yi-Ning; Ma, Xiang; Li, Xiao-Mei; Fu, Zhen-Yan; Xie, Xiang; Liu, Fen; Chen, You; Chen, Bang-Dang; Yu, Zi-Xiang; He, Chun-Hui; Zheng, Ying-Ying; Abudukeremu, Nuremanguli; Abuzhalihan, Jialin; Wang, Yong-Tao

2014-07-29

The optimal cutoff of the waist-to-hip ratio (WHR) among Han adults in Xinjiang, which is located in the center of Asia, is unknown. We aimed to examine the relationship between different WHRs and cardiovascular risk factors among Han adults in Xinjiang, and determine the optimal cutoff of the WHR. The Cardiovascular Risk Survey was conducted from October 2007 to March 2010. A total of 14618 representative participants were selected using a four-stage stratified sampling method. A total of 5757 Han participants were included in the study. The present statistical analysis was restricted to the 5595 Han subjects who had complete anthropometric data. The sensitivity, specificity, and distance on the receiver operating characteristic (ROC) curve in each WHR level were calculated. The shortest distance in the ROC curves was used to determine the optimal cutoff of the WHR for detecting cardiovascular risk factors. In women, the WHR was positively associated with systolic blood pressure, diastolic blood pressure, and serum concentrations of serum total cholesterol. The prevalence of hypertension and hypertriglyceridemia increased as the WHR increased. The same results were not observed among men. The optimal WHR cutoffs for predicting hypertension, diabetes, dyslipidemia and ≥ two of these risk factors for Han adults in Xinjiang were 0.92, 0.92, 0.91, 0.92 in men and 0.88, 0.89, 0.88, 0.89 in women, respectively. Higher cutoffs for the WHR are required in the identification of Han adults aged ≥ 35 years with a high risk of cardiovascular diseases in Xinjiang.

Optimizing Online Suicide Prevention: A Search Engine-Based Tailored Approach.

PubMed

Arendt, Florian; Scherr, Sebastian

2017-11-01

Search engines are increasingly used to seek suicide-related information online, which can serve both harmful and helpful purposes. Google acknowledges this fact and presents a suicide-prevention result for particular search terms. Unfortunately, the result is only presented to a limited number of visitors. Hence, Google is missing the opportunity to provide help to vulnerable people. We propose a two-step approach to a tailored optimization: First, research will identify the risk factors. Second, search engines will reweight algorithms according to the risk factors. In this study, we show that the query share of the search term "poisoning" on Google shows substantial peaks corresponding to peaks in actual suicidal behavior. Accordingly, thresholds for showing the suicide-prevention result should be set to the lowest levels during the spring, on Sundays and Mondays, on New Year's Day, and on Saturdays following Thanksgiving. Search engines can help to save lives globally by utilizing a more tailored approach to suicide prevention.

Benefits and Limitations of Macrotextured Breast Implants and Consensus Recommendations for Optimizing Their Effectiveness.

PubMed

Maxwell, G Patrick; Scheflan, Michael; Spear, Scott; Nava, Maurizio B; Hedén, Per

2014-08-01

Implant texture is an important factor influencing implant selection for breast augmentation. Natrelle Biocell implants are characterized by macrotextured shell surfaces containing irregularly arranged concavities with large open-pore diameters and depths. These properties facilitate adhesion of the implant to the surrounding tissue, thereby promoting implant immobilization. Relative to implants with other surfaces, macrotextured implants offer low rates of capsular contracture; low rates of malposition, rotation, and rippling; and high rates of patient satisfaction. However, macrotextured implants are associated with a slightly higher risk of double capsule and late seroma. The surgeon can minimize these risks with straightforward techniques that encourage tissue adhesion. This report presents experience-based recommendations to optimize the effectiveness of Biocell anatomic implants. The authors discuss the application of best practices to all aspects of the breast implantation process, from implant selection and surgical planning to operative technique and postoperative management. LEVEL OF EVIDENCE 3. © 2014 The American Society for Aesthetic Plastic Surgery, Inc.

PSO/ACO algorithm-based risk assessment of human neural tube defects in Heshun County, China.

PubMed

Liao, Yi Lan; Wang, Jin Feng; Wu, Ji Lei; Wang, Jiao Jiao; Zheng, Xiao Ying

2012-10-01

To develop a new technique for assessing the risk of birth defects, which are a major cause of infant mortality and disability in many parts of the world. The region of interest in this study was Heshun County, the county in China with the highest rate of neural tube defects (NTDs). A hybrid particle swarm optimization/ant colony optimization (PSO/ACO) algorithm was used to quantify the probability of NTDs occurring at villages with no births. The hybrid PSO/ACO algorithm is a form of artificial intelligence adapted for hierarchical classification. It is a powerful technique for modeling complex problems involving impacts of causes. The algorithm was easy to apply, with the accuracy of the results being 69.5%±7.02% at the 95% confidence level. The proposed method is simple to apply, has acceptable fault tolerance, and greatly enhances the accuracy of calculations. Copyright © 2012 The Editorial Board of Biomedical and Environmental Sciences. Published by Elsevier B.V. All rights reserved.

SU-E-T-593: Clinical Evaluation of Direct Aperture Optimization in Head/Neck and Prostate IMRT Treatment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hosini, M; GALAL, M; Emam, I

2014-06-01

Purpose: To investigate the planning and dosimetric advantages of direct aperture optimization (DAO) over beam-let optimization in IMRT treatment of head and neck (H/N) and prostate cancers. Methods: Five Head and Neck as well as five prostate patients were planned using the beamlet optimizer in Elekta-Xio ver 4.6 IMRT treatment planning system. Based on our experience in beamlet IMRT optimization, PTVs in H/N plans were prescribed to 70 Gy delivered by 7 fields. While prostate PTVs were prescribed to 76 Gy with 9 fields. In all plans, fields were set to be equally spaced. All cases were re-planed using Directmore » Aperture optimizer in Prowess Panther ver 5.01 IMRT planning system at same configurations and dose constraints. Plans were evaluated according to ICRU criteria, number of segments, number of monitor units and planning time. Results: For H/N plans, the near maximum dose (D2) and the dose that covers 95% D95 of PTV has improved by 4% in DAO. For organs at risk (OAR), DAO reduced the volume covered by 30% (V30) in spinal cord, right parotid, and left parotid by 60%, 54%, and 53% respectively. This considerable dosimetric quality improvement achieved using 25% less planning time and lower number of segments and monitor units by 46% and 51% respectively. In DAO prostate plans, Both D2 and D95 for the PTV were improved by only 2%. The V30 of the right femur, left femur and bladder were improved by 35%, 15% and 3% respectively. On the contrary, the rectum V30 got even worse by 9%. However, number of monitor units, and number of segments decreased by 20% and 25% respectively. Moreover the planning time reduced significantly too. Conclusion: DAO introduces considerable advantages over the beamlet optimization in regards to organs at risk sparing. However, no significant improvement occurred in most studied PTVs.« less

Genetic investigations on intracranial aneurysm: update and perspectives.

PubMed

Bourcier, Romain; Redon, Richard; Desal, Hubert

2015-04-01

Detection of an intracranial aneurysm (IA) is a common finding in MRI practice. Nowadays, the incidence of unruptured IA seems to be increasing with the continuous evolution of imaging techniques. Important modifiable risk factors for SAH are well defined, but familial history of IA is the best risk marker for the presence of IA. Numerous heritable conditions are associated with IA formation but these syndromes account for less than 1% of all IAs in the population. No diagnostic test based on genetic knowledge is currently available to identify theses mutations and patients who are at higher risk for developing IAs. In the longer term, a more comprehensive understanding of independent and interdependent molecular pathways germane to IA formation and rupture may guide the physician in developing targeted therapies and optimizing prognostic risk assessment. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

The roles of exercise and fall risk reduction in the prevention of osteoporosis.

PubMed

Henderson, N K; White, C P; Eisman, J A

1998-06-01

In summary, the optimal model for the prevention of osteoporotic fractures includes maximization and maintenance of bone strength and minimization of trauma. Numerous determinants of each have been identified, but further work to develop preventative strategies based on these determinants remains to be undertaken. Physical activity is a determinant of peak BMD. There also is evidence that activity during growth modulates the external geometry and trabecular architecture, potentially enhancing skeletal strength, while during the adult years activity may reduce age-related bone loss. The magnitude of the effect of a 7% to 8% increase in peak BMD, if maintained through the adult years, could translate to a 1.5-fold reduction in fracture risk. Moreover, in the older population, appropriate forms of exercise could reduce the risk of falling and, thus, further reduce fracture risk. These data must be considered as preliminary in view of the paucity of long-term fracture outcome data from randomized clinical trials. However, current information suggests that the optimal form of exercise to achieve these objectives may vary through life. Vigorous physical activity (including weight-bearing, resistance, and impact components) during childhood may maximize peak BMD. This type of activity seems optimal through the young adult years, but as inevitable age-related degeneration occurs, activity modification to limit the impact component of exercise may become necessary. In the elderly, progressive strength training has been demonstrated to be a safe and effective form of exercise that reduces risk factors for falling and may also enhance BMD. In the frail elderly, activity to improve balance and confidence also may be valuable. Group activities such as Tai Chi may be cost-effective. Precise prescriptions must await the outcome of well-designed, controlled longitudinal studies that include fracture as an outcome. However, increased physical activity seems to be a sensible component of strategies to reduce osteoporotic fracture.